WorldWideScience

Sample records for variables statistical analyses

  1. Statistical analyses of variability/reproducibility of environmentally assisted cyclic crack growth rate data utilizing JAERI Material Performance Database (JMPD)

    International Nuclear Information System (INIS)

    Tsuji, Hirokazu; Yokoyama, Norio; Nakajima, Hajime; Kondo, Tatsuo

    1993-05-01

    Statistical analyses were conducted by using the cyclic crack growth rate data for pressure vessel steels stored in the JAERI Material Performance Database (JMPD), and comparisons were made on variability and/or reproducibility of the data between obtained by ΔK-increasing and by ΔK-constant type tests. Based on the results of the statistical analyses, it was concluded that ΔK-constant type tests are generally superior to the commonly used ΔK-increasing type ones from the viewpoint of variability and/or reproducibility of the data. Such a tendency was more pronounced in the tests conducted in simulated LWR primary coolants than those in air. (author)

  2. An innovative statistical approach for analysing non-continuous variables in environmental monitoring: assessing temporal trends of TBT pollution.

    Science.gov (United States)

    Santos, José António; Galante-Oliveira, Susana; Barroso, Carlos

    2011-03-01

    The current work presents an innovative statistical approach to model ordinal variables in environmental monitoring studies. An ordinal variable has values that can only be compared as "less", "equal" or "greater" and it is not possible to have information about the size of the difference between two particular values. The example of ordinal variable under this study is the vas deferens sequence (VDS) used in imposex (superimposition of male sexual characters onto prosobranch females) field assessment programmes for monitoring tributyltin (TBT) pollution. The statistical methodology presented here is the ordered logit regression model. It assumes that the VDS is an ordinal variable whose values match up a process of imposex development that can be considered continuous in both biological and statistical senses and can be described by a latent non-observable continuous variable. This model was applied to the case study of Nucella lapillus imposex monitoring surveys conducted in the Portuguese coast between 2003 and 2008 to evaluate the temporal evolution of TBT pollution in this country. In order to produce more reliable conclusions, the proposed model includes covariates that may influence the imposex response besides TBT (e.g. the shell size). The model also provides an analysis of the environmental risk associated to TBT pollution by estimating the probability of the occurrence of females with VDS ≥ 2 in each year, according to OSPAR criteria. We consider that the proposed application of this statistical methodology has a great potential in environmental monitoring whenever there is the need to model variables that can only be assessed through an ordinal scale of values.

  3. Statistical analyses of extreme food habits

    International Nuclear Information System (INIS)

    Breuninger, M.; Neuhaeuser-Berthold, M.

    2000-01-01

    This report is a summary of the results of the project ''Statistical analyses of extreme food habits'', which was ordered from the National Office for Radiation Protection as a contribution to the amendment of the ''General Administrative Regulation to paragraph 45 of the Decree on Radiation Protection: determination of the radiation exposition by emission of radioactive substances from facilities of nuclear technology''. Its aim is to show if the calculation of the radiation ingested by 95% of the population by food intake, like it is planned in a provisional draft, overestimates the true exposure. If such an overestimation exists, the dimension of it should be determined. It was possible to prove the existence of this overestimation but its dimension could only roughly be estimated. To identify the real extent of it, it is necessary to include the specific activities of the nuclides, which were not available for this investigation. In addition to this the report shows how the amounts of food consumption of different groups of foods influence each other and which connections between these amounts should be taken into account, in order to estimate the radiation exposition as precise as possible. (orig.) [de

  4. Statistical variability of hydro-meteorological variables as indicators ...

    African Journals Online (AJOL)

    Statistical variability of hydro-meteorological variables as indicators of climate change in north-east Sokoto-Rima basin, Nigeria. ... water resources development including water supply project, agriculture and tourism in the study area. Key word: Climate change, Climatic variability, Actual evapotranspiration, Global warming ...

  5. Applied statistics a handbook of BMDP analyses

    CERN Document Server

    Snell, E J

    1987-01-01

    This handbook is a realization of a long term goal of BMDP Statistical Software. As the software supporting statistical analysis has grown in breadth and depth to the point where it can serve many of the needs of accomplished statisticians it can also serve as an essential support to those needing to expand their knowledge of statistical applications. Statisticians should not be handicapped by heavy computation or by the lack of needed options. When Applied Statistics, Principle and Examples by Cox and Snell appeared we at BMDP were impressed with the scope of the applications discussed and felt that many statisticians eager to expand their capabilities in handling such problems could profit from having the solutions carried further, to get them started and guided to a more advanced level in problem solving. Who would be better to undertake that task than the authors of Applied Statistics? A year or two later discussions with David Cox and Joyce Snell at Imperial College indicated that a wedding of the proble...

  6. Statistical identification of effective input variables

    International Nuclear Information System (INIS)

    Vaurio, J.K.

    1982-09-01

    A statistical sensitivity analysis procedure has been developed for ranking the input data of large computer codes in the order of sensitivity-importance. The method is economical for large codes with many input variables, since it uses a relatively small number of computer runs. No prior judgemental elimination of input variables is needed. The sceening method is based on stagewise correlation and extensive regression analysis of output values calculated with selected input value combinations. The regression process deals with multivariate nonlinear functions, and statistical tests are also available for identifying input variables that contribute to threshold effects, i.e., discontinuities in the output variables. A computer code SCREEN has been developed for implementing the screening techniques. The efficiency has been demonstrated by several examples and applied to a fast reactor safety analysis code (Venus-II). However, the methods and the coding are general and not limited to such applications

  7. Methodology development for statistical evaluation of reactor safety analyses

    International Nuclear Information System (INIS)

    Mazumdar, M.; Marshall, J.A.; Chay, S.C.; Gay, R.

    1976-07-01

    In February 1975, Westinghouse Electric Corporation, under contract to Electric Power Research Institute, started a one-year program to develop methodology for statistical evaluation of nuclear-safety-related engineering analyses. The objectives of the program were to develop an understanding of the relative efficiencies of various computational methods which can be used to compute probability distributions of output variables due to input parameter uncertainties in analyses of design basis events for nuclear reactors and to develop methods for obtaining reasonably accurate estimates of these probability distributions at an economically feasible level. A series of tasks was set up to accomplish these objectives. Two of the tasks were to investigate the relative efficiencies and accuracies of various Monte Carlo and analytical techniques for obtaining such estimates for a simple thermal-hydraulic problem whose output variable of interest is given in a closed-form relationship of the input variables and to repeat the above study on a thermal-hydraulic problem in which the relationship between the predicted variable and the inputs is described by a short-running computer program. The purpose of the report presented is to document the results of the investigations completed under these tasks, giving the rationale for choices of techniques and problems, and to present interim conclusions

  8. Hydrometeorological and statistical analyses of heavy rainfall in Midwestern USA

    Science.gov (United States)

    Thorndahl, S.; Smith, J. A.; Krajewski, W. F.

    2012-04-01

    During the last two decades the mid-western states of the United States of America has been largely afflicted by heavy flood producing rainfall. Several of these storms seem to have similar hydrometeorological properties in terms of pattern, track, evolution, life cycle, clustering, etc. which raise the question if it is possible to derive general characteristics of the space-time structures of these heavy storms. This is important in order to understand hydrometeorological features, e.g. how storms evolve and with what frequency we can expect extreme storms to occur. In the literature, most studies of extreme rainfall are based on point measurements (rain gauges). However, with high resolution and quality radar observation periods exceeding more than two decades, it is possible to do long-term spatio-temporal statistical analyses of extremes. This makes it possible to link return periods to distributed rainfall estimates and to study precipitation structures which cause floods. However, doing these statistical frequency analyses of rainfall based on radar observations introduces some different challenges, converting radar reflectivity observations to "true" rainfall, which are not problematic doing traditional analyses on rain gauge data. It is for example difficult to distinguish reflectivity from high intensity rain from reflectivity from other hydrometeors such as hail, especially using single polarization radars which are used in this study. Furthermore, reflectivity from bright band (melting layer) should be discarded and anomalous propagation should be corrected in order to produce valid statistics of extreme radar rainfall. Other challenges include combining observations from several radars to one mosaic, bias correction against rain gauges, range correction, ZR-relationships, etc. The present study analyzes radar rainfall observations from 1996 to 2011 based the American NEXRAD network of radars over an area covering parts of Iowa, Wisconsin, Illinois, and

  9. Statistical analyses of conserved features of genomic islands in bacteria.

    Science.gov (United States)

    Guo, F-B; Xia, Z-K; Wei, W; Zhao, H-L

    2014-03-17

    We performed statistical analyses of five conserved features of genomic islands of bacteria. Analyses were made based on 104 known genomic islands, which were identified by comparative methods. Four of these features include sequence size, abnormal G+C content, flanking tRNA gene, and embedded mobility gene, which are frequently investigated. One relatively new feature, G+C homogeneity, was also investigated. Among the 104 known genomic islands, 88.5% were found to fall in the typical length of 10-200 kb and 80.8% had G+C deviations with absolute values larger than 2%. For the 88 genomic islands whose hosts have been sequenced and annotated, 52.3% of them were found to have flanking tRNA genes and 64.7% had embedded mobility genes. For the homogeneity feature, 85% had an h homogeneity index less than 0.1, indicating that their G+C content is relatively uniform. Taking all the five features into account, 87.5% of 88 genomic islands had three of them. Only one genomic island had only one conserved feature and none of the genomic islands had zero features. These statistical results should help to understand the general structure of known genomic islands. We found that larger genomic islands tend to have relatively small G+C deviations relative to absolute values. For example, the absolute G+C deviations of 9 genomic islands longer than 100,000 bp were all less than 5%. This is a novel but reasonable result given that larger genomic islands should have greater restrictions in their G+C contents, in order to maintain the stable G+C content of the recipient genome.

  10. Statistical reliability analyses of two wood plastic composite extrusion processes

    International Nuclear Information System (INIS)

    Crookston, Kevin A.; Mark Young, Timothy; Harper, David; Guess, Frank M.

    2011-01-01

    Estimates of the reliability of wood plastic composites (WPC) are explored for two industrial extrusion lines. The goal of the paper is to use parametric and non-parametric analyses to examine potential differences in the WPC metrics of reliability for the two extrusion lines that may be helpful for use by the practitioner. A parametric analysis of the extrusion lines reveals some similarities and disparities in the best models; however, a non-parametric analysis reveals unique and insightful differences between Kaplan-Meier survival curves for the modulus of elasticity (MOE) and modulus of rupture (MOR) of the WPC industrial data. The distinctive non-parametric comparisons indicate the source of the differences in strength between the 10.2% and 48.0% fractiles [3,183-3,517 MPa] for MOE and for MOR between the 2.0% and 95.1% fractiles [18.9-25.7 MPa]. Distribution fitting as related to selection of the proper statistical methods is discussed with relevance to estimating the reliability of WPC. The ability to detect statistical differences in the product reliability of WPC between extrusion processes may benefit WPC producers in improving product reliability and safety of this widely used house-decking product. The approach can be applied to many other safety and complex system lifetime comparisons.

  11. Statistical power analyses using G*Power 3.1: tests for correlation and regression analyses.

    Science.gov (United States)

    Faul, Franz; Erdfelder, Edgar; Buchner, Axel; Lang, Albert-Georg

    2009-11-01

    G*Power is a free power analysis program for a variety of statistical tests. We present extensions and improvements of the version introduced by Faul, Erdfelder, Lang, and Buchner (2007) in the domain of correlation and regression analyses. In the new version, we have added procedures to analyze the power of tests based on (1) single-sample tetrachoric correlations, (2) comparisons of dependent correlations, (3) bivariate linear regression, (4) multiple linear regression based on the random predictor model, (5) logistic regression, and (6) Poisson regression. We describe these new features and provide a brief introduction to their scope and handling.

  12. Non-Statistical Methods of Analysing of Bankruptcy Risk

    Directory of Open Access Journals (Sweden)

    Pisula Tomasz

    2015-06-01

    Full Text Available The article focuses on assessing the effectiveness of a non-statistical approach to bankruptcy modelling in enterprises operating in the logistics sector. In order to describe the issue more comprehensively, the aforementioned prediction of the possible negative results of business operations was carried out for companies functioning in the Polish region of Podkarpacie, and in Slovakia. The bankruptcy predictors selected for the assessment of companies operating in the logistics sector included 28 financial indicators characterizing these enterprises in terms of their financial standing and management effectiveness. The purpose of the study was to identify factors (models describing the bankruptcy risk in enterprises in the context of their forecasting effectiveness in a one-year and two-year time horizon. In order to assess their practical applicability the models were carefully analysed and validated. The usefulness of the models was assessed in terms of their classification properties, and the capacity to accurately identify enterprises at risk of bankruptcy and healthy companies as well as proper calibration of the models to the data from training sample sets.

  13. A weighted U statistic for association analyses considering genetic heterogeneity.

    Science.gov (United States)

    Wei, Changshuai; Elston, Robert C; Lu, Qing

    2016-07-20

    Converging evidence suggests that common complex diseases with the same or similar clinical manifestations could have different underlying genetic etiologies. While current research interests have shifted toward uncovering rare variants and structural variations predisposing to human diseases, the impact of heterogeneity in genetic studies of complex diseases has been largely overlooked. Most of the existing statistical methods assume the disease under investigation has a homogeneous genetic effect and could, therefore, have low power if the disease undergoes heterogeneous pathophysiological and etiological processes. In this paper, we propose a heterogeneity-weighted U (HWU) method for association analyses considering genetic heterogeneity. HWU can be applied to various types of phenotypes (e.g., binary and continuous) and is computationally efficient for high-dimensional genetic data. Through simulations, we showed the advantage of HWU when the underlying genetic etiology of a disease was heterogeneous, as well as the robustness of HWU against different model assumptions (e.g., phenotype distributions). Using HWU, we conducted a genome-wide analysis of nicotine dependence from the Study of Addiction: Genetics and Environments dataset. The genome-wide analysis of nearly one million genetic markers took 7h, identifying heterogeneous effects of two new genes (i.e., CYP3A5 and IKBKB) on nicotine dependence. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

  14. Statistical Dependence of Pipe Breaks on Explanatory Variables

    Directory of Open Access Journals (Sweden)

    Patricia Gómez-Martínez

    2017-02-01

    Full Text Available Aging infrastructure is the main challenge currently faced by water suppliers. Estimation of assets lifetime requires reliable criteria to plan assets repair and renewal strategies. To do so, pipe break prediction is one of the most important inputs. This paper analyzes the statistical dependence of pipe breaks on explanatory variables, determining their optimal combination and quantifying their influence on failure prediction accuracy. A large set of registered data from Madrid water supply network, managed by Canal de Isabel II, has been filtered, classified and studied. Several statistical Bayesian models have been built and validated from the available information with a technique that combines reference periods of time as well as geographical location. Statistical models of increasing complexity are built from zero up to five explanatory variables following two approaches: a set of independent variables or a combination of two joint variables plus an additional number of independent variables. With the aim of finding the variable combination that provides the most accurate prediction, models are compared following an objective validation procedure based on the model skill to predict the number of pipe breaks in a large set of geographical locations. As expected, model performance improves as the number of explanatory variables increases. However, the rate of improvement is not constant. Performance metrics improve significantly up to three variables, but the tendency is softened for higher order models, especially in trunk mains where performance is reduced. Slight differences are found between trunk mains and distribution lines when selecting the most influent variables and models.

  15. Statistical and extra-statistical considerations in differential item functioning analyses

    Directory of Open Access Journals (Sweden)

    G. K. Huysamen

    2004-10-01

    Full Text Available This article briefly describes the main procedures for performing differential item functioning (DIF analyses and points out some of the statistical and extra-statistical implications of these methods. Research findings on the sources of DIF, including those associated with translated tests, are reviewed. As DIF analyses are oblivious of correlations between a test and relevant criteria, the elimination of differentially functioning items does not necessarily improve predictive validity or reduce any predictive bias. The implications of the results of past DIF research for test development in the multilingual and multi-cultural South African society are considered. Opsomming Hierdie artikel beskryf kortliks die hoofprosedures vir die ontleding van differensiële itemfunksionering (DIF en verwys na sommige van die statistiese en buite-statistiese implikasies van hierdie metodes. ’n Oorsig word verskaf van navorsingsbevindings oor die bronne van DIF, insluitend dié by vertaalde toetse. Omdat DIF-ontledings nie die korrelasies tussen ’n toets en relevante kriteria in ag neem nie, sal die verwydering van differensieel-funksionerende items nie noodwendig voorspellingsgeldigheid verbeter of voorspellingsydigheid verminder nie. Die implikasies van vorige DIF-navorsingsbevindings vir toetsontwikkeling in die veeltalige en multikulturele Suid-Afrikaanse gemeenskap word oorweeg.

  16. Statistical Analyses of Scatterplots to Identify Important Factors in Large-Scale Simulations

    Energy Technology Data Exchange (ETDEWEB)

    Kleijnen, J.P.C.; Helton, J.C.

    1999-04-01

    The robustness of procedures for identifying patterns in scatterplots generated in Monte Carlo sensitivity analyses is investigated. These procedures are based on attempts to detect increasingly complex patterns in the scatterplots under consideration and involve the identification of (1) linear relationships with correlation coefficients, (2) monotonic relationships with rank correlation coefficients, (3) trends in central tendency as defined by means, medians and the Kruskal-Wallis statistic, (4) trends in variability as defined by variances and interquartile ranges, and (5) deviations from randomness as defined by the chi-square statistic. The following two topics related to the robustness of these procedures are considered for a sequence of example analyses with a large model for two-phase fluid flow: the presence of Type I and Type II errors, and the stability of results obtained with independent Latin hypercube samples. Observations from analysis include: (1) Type I errors are unavoidable, (2) Type II errors can occur when inappropriate analysis procedures are used, (3) physical explanations should always be sought for why statistical procedures identify variables as being important, and (4) the identification of important variables tends to be stable for independent Latin hypercube samples.

  17. Statistical screening of input variables in a complex computer code

    International Nuclear Information System (INIS)

    Krieger, T.J.

    1982-01-01

    A method is presented for ''statistical screening'' of input variables in a complex computer code. The object is to determine the ''effective'' or important input variables by estimating the relative magnitudes of their associated sensitivity coefficients. This is accomplished by performing a numerical experiment consisting of a relatively small number of computer runs with the code followed by a statistical analysis of the results. A formula for estimating the sensitivity coefficients is derived. Reference is made to an earlier work in which the method was applied to a complex reactor code with good results

  18. Understanding and forecasting polar stratospheric variability with statistical models

    Directory of Open Access Journals (Sweden)

    C. Blume

    2012-07-01

    Full Text Available The variability of the north-polar stratospheric vortex is a prominent aspect of the middle atmosphere. This work investigates a wide class of statistical models with respect to their ability to model geopotential and temperature anomalies, representing variability in the polar stratosphere. Four partly nonstationary, nonlinear models are assessed: linear discriminant analysis (LDA; a cluster method based on finite elements (FEM-VARX; a neural network, namely the multi-layer perceptron (MLP; and support vector regression (SVR. These methods model time series by incorporating all significant external factors simultaneously, including ENSO, QBO, the solar cycle, volcanoes, to then quantify their statistical importance. We show that variability in reanalysis data from 1980 to 2005 is successfully modeled. The period from 2005 to 2011 can be hindcasted to a certain extent, where MLP performs significantly better than the remaining models. However, variability remains that cannot be statistically hindcasted within the current framework, such as the unexpected major warming in January 2009. Finally, the statistical model with the best generalization performance is used to predict a winter 2011/12 with warm and weak vortex conditions. A vortex breakdown is predicted for late January, early February 2012.

  19. Temporal scaling and spatial statistical analyses of groundwater level fluctuations

    Science.gov (United States)

    Sun, H.; Yuan, L., Sr.; Zhang, Y.

    2017-12-01

    Natural dynamics such as groundwater level fluctuations can exhibit multifractionality and/or multifractality due likely to multi-scale aquifer heterogeneity and controlling factors, whose statistics requires efficient quantification methods. This study explores multifractionality and non-Gaussian properties in groundwater dynamics expressed by time series of daily level fluctuation at three wells located in the lower Mississippi valley, after removing the seasonal cycle in the temporal scaling and spatial statistical analysis. First, using the time-scale multifractional analysis, a systematic statistical method is developed to analyze groundwater level fluctuations quantified by the time-scale local Hurst exponent (TS-LHE). Results show that the TS-LHE does not remain constant, implying the fractal-scaling behavior changing with time and location. Hence, we can distinguish the potentially location-dependent scaling feature, which may characterize the hydrology dynamic system. Second, spatial statistical analysis shows that the increment of groundwater level fluctuations exhibits a heavy tailed, non-Gaussian distribution, which can be better quantified by a Lévy stable distribution. Monte Carlo simulations of the fluctuation process also show that the linear fractional stable motion model can well depict the transient dynamics (i.e., fractal non-Gaussian property) of groundwater level, while fractional Brownian motion is inadequate to describe natural processes with anomalous dynamics. Analysis of temporal scaling and spatial statistics therefore may provide useful information and quantification to understand further the nature of complex dynamics in hydrology.

  20. The intervals method: a new approach to analyse finite element outputs using multivariate statistics

    Directory of Open Access Journals (Sweden)

    Jordi Marcé-Nogué

    2017-10-01

    Full Text Available Background In this paper, we propose a new method, named the intervals’ method, to analyse data from finite element models in a comparative multivariate framework. As a case study, several armadillo mandibles are analysed, showing that the proposed method is useful to distinguish and characterise biomechanical differences related to diet/ecomorphology. Methods The intervals’ method consists of generating a set of variables, each one defined by an interval of stress values. Each variable is expressed as a percentage of the area of the mandible occupied by those stress values. Afterwards these newly generated variables can be analysed using multivariate methods. Results Applying this novel method to the biological case study of whether armadillo mandibles differ according to dietary groups, we show that the intervals’ method is a powerful tool to characterize biomechanical performance and how this relates to different diets. This allows us to positively discriminate between specialist and generalist species. Discussion We show that the proposed approach is a useful methodology not affected by the characteristics of the finite element mesh. Additionally, the positive discriminating results obtained when analysing a difficult case study suggest that the proposed method could be a very useful tool for comparative studies in finite element analysis using multivariate statistical approaches.

  1. The intervals method: a new approach to analyse finite element outputs using multivariate statistics

    Science.gov (United States)

    De Esteban-Trivigno, Soledad; Püschel, Thomas A.; Fortuny, Josep

    2017-01-01

    Background In this paper, we propose a new method, named the intervals’ method, to analyse data from finite element models in a comparative multivariate framework. As a case study, several armadillo mandibles are analysed, showing that the proposed method is useful to distinguish and characterise biomechanical differences related to diet/ecomorphology. Methods The intervals’ method consists of generating a set of variables, each one defined by an interval of stress values. Each variable is expressed as a percentage of the area of the mandible occupied by those stress values. Afterwards these newly generated variables can be analysed using multivariate methods. Results Applying this novel method to the biological case study of whether armadillo mandibles differ according to dietary groups, we show that the intervals’ method is a powerful tool to characterize biomechanical performance and how this relates to different diets. This allows us to positively discriminate between specialist and generalist species. Discussion We show that the proposed approach is a useful methodology not affected by the characteristics of the finite element mesh. Additionally, the positive discriminating results obtained when analysing a difficult case study suggest that the proposed method could be a very useful tool for comparative studies in finite element analysis using multivariate statistical approaches. PMID:29043107

  2. Using statistical inference for decision making in best estimate analyses

    International Nuclear Information System (INIS)

    Sermer, P.; Weaver, K.; Hoppe, F.; Olive, C.; Quach, D.

    2008-01-01

    For broad classes of safety analysis problems, one needs to make decisions when faced with randomly varying quantities which are also subject to errors. The means for doing this involves a statistical approach which takes into account the nature of the physical problems, and the statistical constraints they impose. We describe the methodology for doing this which has been developed at Nuclear Safety Solutions, and we draw some comparisons to other methods which are commonly used in Canada and internationally. Our methodology has the advantages of being robust and accurate and compares favourably to other best estimate methods. (author)

  3. Additional methodology development for statistical evaluation of reactor safety analyses

    International Nuclear Information System (INIS)

    Marshall, J.A.; Shore, R.W.; Chay, S.C.; Mazumdar, M.

    1977-03-01

    The project described is motivated by the desire for methods to quantify uncertainties and to identify conservatisms in nuclear power plant safety analysis. The report examines statistical methods useful for assessing the probability distribution of output response from complex nuclear computer codes, considers sensitivity analysis and several other topics, and also sets the path for using the developed methods for realistic assessment of the design basis accident

  4. A Statistical Analysis of Cointegration for I(2) Variables

    DEFF Research Database (Denmark)

    Johansen, Søren

    1995-01-01

    be conducted using the ¿ sup2/sup distribution. It is shown to what extent inference on the cointegration ranks can be conducted using the tables already prepared for the analysis of cointegration of I(1) variables. New tables are needed for the test statistics to control the size of the tests. This paper...... contains a multivariate test for the existence of I(2) variables. This test is illustrated using a data set consisting of U.K. and foreign prices and interest rates as well as the exchange rate....

  5. Variability aware compact model characterization for statistical circuit design optimization

    Science.gov (United States)

    Qiao, Ying; Qian, Kun; Spanos, Costas J.

    2012-03-01

    Variability modeling at the compact transistor model level can enable statistically optimized designs in view of limitations imposed by the fabrication technology. In this work we propose an efficient variabilityaware compact model characterization methodology based on the linear propagation of variance. Hierarchical spatial variability patterns of selected compact model parameters are directly calculated from transistor array test structures. This methodology has been implemented and tested using transistor I-V measurements and the EKV-EPFL compact model. Calculation results compare well to full-wafer direct model parameter extractions. Further studies are done on the proper selection of both compact model parameters and electrical measurement metrics used in the method.

  6. Statistical validity of using ratio variables in human kinetics research.

    Science.gov (United States)

    Liu, Yuanlong; Schutz, Robert W

    2003-09-01

    The purposes of this study were to investigate the validity of the simple ratio and three alternative deflation models and examine how the variation of the numerator and denominator variables affects the reliability of a ratio variable. A simple ratio and three alternative deflation models were fitted to four empirical data sets, and common criteria were applied to determine the best model for deflation. Intraclass correlation was used to examine the component effect on the reliability of a ratio variable. The results indicate that the validity, of a deflation model depends on the statistical characteristics of the particular component variables used, and an optimal deflation model for all ratio variables may not exist. Therefore, it is recommended that different models be fitted to each empirical data set to determine the best deflation model. It was found that the reliability of a simple ratio is affected by the coefficients of variation and the within- and between-trial correlations between the numerator and denominator variables. It was recommended that researchers should compute the reliability of the derived ratio scores and not assume that strong reliabilities in the numerator and denominator measures automatically lead to high reliability in the ratio measures.

  7. Theoretical statistics of zero-age cataclysmic variables

    International Nuclear Information System (INIS)

    Politano, M.J.

    1988-01-01

    The distribution of the white dwarf masses, the distribution of the mass ratios and the distribution of the orbital periods in cataclysmic variables which are forming at the present time are calculated. These systems are referred to as zero-age cataclysmic variables. The results show that 60% of the systems being formed contain helium white dwarfs and 40% contain carbon-oxygen white dwarfs. The mean dwarf mass in those systems containing helium white dwarfs is 0.34. The mean white dwarf mass in those systems containing carbon-oxygen white dwarfs is 0.75. The orbital period distribution identifies four main classes of zero-age cataclysmic variables: (1) short-period systems containing helium white dwarfs, (2) systems containing carbon-oxygen white dwarfs whose secondaries are convectively stable against rapid mass transfer to the white dwarf, (3) systems containing carbon-oxygen white dwarfs whose secondaries are radiatively stable against rapid mass transfer to the white dwarf and (4) long period systems with evolved secondaries. The white dwarf mass distribution in zero-age cataclysmic variables has direct application to the calculation of the frequency of outburst in classical novae as a function of the mass of the white dwarf. The method developed in this thesis to calculate the distributions of the orbital parameters in zero-age cataclysmic variables can be used to calculate theoretical statistics of any class of binary systems. This method provides a theoretical framework from which to investigate the statistical properties and the evolution of the orbital parameters of binary systems

  8. Statistical conditional sampling for variable-resolution video compression.

    Directory of Open Access Journals (Sweden)

    Alexander Wong

    Full Text Available In this study, we investigate a variable-resolution approach to video compression based on Conditional Random Field and statistical conditional sampling in order to further improve compression rate while maintaining high-quality video. In the proposed approach, representative key-frames within a video shot are identified and stored at full resolution. The remaining frames within the video shot are stored and compressed at a reduced resolution. At the decompression stage, a region-based dictionary is constructed from the key-frames and used to restore the reduced resolution frames to the original resolution via statistical conditional sampling. The sampling approach is based on the conditional probability of the CRF modeling by use of the constructed dictionary. Experimental results show that the proposed variable-resolution approach via statistical conditional sampling has potential for improving compression rates when compared to compressing the video at full resolution, while achieving higher video quality when compared to compressing the video at reduced resolution.

  9. Statistical reporting errors and collaboration on statistical analyses in psychological science

    NARCIS (Netherlands)

    Veldkamp, C.L.S.; Nuijten, M.B.; Dominguez Alvarez, L.; van Assen, M.A.L.M.; Wicherts, J.M.

    2014-01-01

    Statistical analysis is error prone. A best practice for researchers using statistics would therefore be to share data among co-authors, allowing double-checking of executed tasks just as co-pilots do in aviation. To document the extent to which this ‘co-piloting’ currently occurs in psychology, we

  10. Transformation (normalization) of slope gradient and surface curvatures, automated for statistical analyses from DEMs

    Science.gov (United States)

    Csillik, O.; Evans, I. S.; Drăguţ, L.

    2015-03-01

    Automated procedures are developed to alleviate long tails in frequency distributions of morphometric variables. They minimize the skewness of slope gradient frequency distributions, and modify the kurtosis of profile and plan curvature distributions toward that of the Gaussian (normal) model. Box-Cox (for slope) and arctangent (for curvature) transformations are tested on nine digital elevation models (DEMs) of varying origin and resolution, and different landscapes, and shown to be effective. Resulting histograms are illustrated and show considerable improvements over those for previously recommended slope transformations (sine, square root of sine, and logarithm of tangent). Unlike previous approaches, the proposed method evaluates the frequency distribution of slope gradient values in a given area and applies the most appropriate transform if required. Sensitivity of the arctangent transformation is tested, showing that Gaussian-kurtosis transformations are acceptable also in terms of histogram shape. Cube root transformations of curvatures produced bimodal histograms. The transforms are applicable to morphometric variables and many others with skewed or long-tailed distributions. By avoiding long tails and outliers, they permit parametric statistics such as correlation, regression and principal component analyses to be applied, with greater confidence that requirements for linearity, additivity and even scatter of residuals (constancy of error variance) are likely to be met. It is suggested that such transformations should be routinely applied in all parametric analyses of long-tailed variables. Our Box-Cox and curvature automated transformations are based on a Python script, implemented as an easy-to-use script tool in ArcGIS.

  11. PROCESS VARIABILITY REDUCTION THROUGH STATISTICAL PROCESS CONTROL FOR QUALITY IMPROVEMENT

    Directory of Open Access Journals (Sweden)

    B.P. Mahesh

    2010-09-01

    Full Text Available Quality has become one of the most important customer decision factors in the selection among the competing product and services. Consequently, understanding and improving quality is a key factor leading to business success, growth and an enhanced competitive position. Hence quality improvement program should be an integral part of the overall business strategy. According to TQM, the effective way to improve the Quality of the product or service is to improve the process used to build the product. Hence, TQM focuses on process, rather than results as the results are driven by the processes. Many techniques are available for quality improvement. Statistical Process Control (SPC is one such TQM technique which is widely accepted for analyzing quality problems and improving the performance of the production process. This article illustrates the step by step procedure adopted at a soap manufacturing company to improve the Quality by reducing process variability using Statistical Process Control.

  12. Multivariate statistical analyses demonstrate unique host immune responses to single and dual lentiviral infection.

    Directory of Open Access Journals (Sweden)

    Sunando Roy

    2009-10-01

    Full Text Available Feline immunodeficiency virus (FIV and human immunodeficiency virus (HIV are recently identified lentiviruses that cause progressive immune decline and ultimately death in infected cats and humans. It is of great interest to understand how to prevent immune system collapse caused by these lentiviruses. We recently described that disease caused by a virulent FIV strain in cats can be attenuated if animals are first infected with a feline immunodeficiency virus derived from a wild cougar. The detailed temporal tracking of cat immunological parameters in response to two viral infections resulted in high-dimensional datasets containing variables that exhibit strong co-variation. Initial analyses of these complex data using univariate statistical techniques did not account for interactions among immunological response variables and therefore potentially obscured significant effects between infection state and immunological parameters.Here, we apply a suite of multivariate statistical tools, including Principal Component Analysis, MANOVA and Linear Discriminant Analysis, to temporal immunological data resulting from FIV superinfection in domestic cats. We investigated the co-variation among immunological responses, the differences in immune parameters among four groups of five cats each (uninfected, single and dual infected animals, and the "immune profiles" that discriminate among them over the first four weeks following superinfection. Dual infected cats mount an immune response by 24 days post superinfection that is characterized by elevated levels of CD8 and CD25 cells and increased expression of IL4 and IFNgamma, and FAS. This profile discriminates dual infected cats from cats infected with FIV alone, which show high IL-10 and lower numbers of CD8 and CD25 cells.Multivariate statistical analyses demonstrate both the dynamic nature of the immune response to FIV single and dual infection and the development of a unique immunological profile in dual

  13. Statistical Reporting Errors and Collaboration on Statistical Analyses in Psychological Science.

    Science.gov (United States)

    Veldkamp, Coosje L S; Nuijten, Michèle B; Dominguez-Alvarez, Linda; van Assen, Marcel A L M; Wicherts, Jelte M

    2014-01-01

    Statistical analysis is error prone. A best practice for researchers using statistics would therefore be to share data among co-authors, allowing double-checking of executed tasks just as co-pilots do in aviation. To document the extent to which this 'co-piloting' currently occurs in psychology, we surveyed the authors of 697 articles published in six top psychology journals and asked them whether they had collaborated on four aspects of analyzing data and reporting results, and whether the described data had been shared between the authors. We acquired responses for 49.6% of the articles and found that co-piloting on statistical analysis and reporting results is quite uncommon among psychologists, while data sharing among co-authors seems reasonably but not completely standard. We then used an automated procedure to study the prevalence of statistical reporting errors in the articles in our sample and examined the relationship between reporting errors and co-piloting. Overall, 63% of the articles contained at least one p-value that was inconsistent with the reported test statistic and the accompanying degrees of freedom, and 20% of the articles contained at least one p-value that was inconsistent to such a degree that it may have affected decisions about statistical significance. Overall, the probability that a given p-value was inconsistent was over 10%. Co-piloting was not found to be associated with reporting errors.

  14. "What If" Analyses: Ways to Interpret Statistical Significance Test Results Using EXCEL or "R"

    Science.gov (United States)

    Ozturk, Elif

    2012-01-01

    The present paper aims to review two motivations to conduct "what if" analyses using Excel and "R" to understand the statistical significance tests through the sample size context. "What if" analyses can be used to teach students what statistical significance tests really do and in applied research either prospectively to estimate what sample size…

  15. Statistical analyses of scatterplots to identify important factors in large-scale simulations, 1: Review and comparison of techniques

    International Nuclear Information System (INIS)

    Kleijnen, J.P.C.; Helton, J.C.

    1999-01-01

    Procedures for identifying patterns in scatterplots generated in Monte Carlo sensitivity analyses are described and illustrated. These procedures attempt to detect increasingly complex patterns in scatterplots and involve the identification of (i) linear relationships with correlation coefficients, (ii) monotonic relationships with rank correlation coefficients, (iii) trends in central tendency as defined by means, medians and the Kruskal-Wallis statistic, (iv) trends in variability as defined by variances and interquartile ranges, and (v) deviations from randomness as defined by the chi-square statistic. A sequence of example analyses with a large model for two-phase fluid flow illustrates how the individual procedures can differ in the variables that they identify as having effects on particular model outcomes. The example analyses indicate that the use of a sequence of procedures is a good analysis strategy and provides some assurance that an important effect is not overlooked

  16. Statistical Data Analyses of Trace Chemical, Biochemical, and Physical Analytical Signatures

    Energy Technology Data Exchange (ETDEWEB)

    Udey, Ruth Norma [Michigan State Univ., East Lansing, MI (United States)

    2013-01-01

    Analytical and bioanalytical chemistry measurement results are most meaningful when interpreted using rigorous statistical treatments of the data. The same data set may provide many dimensions of information depending on the questions asked through the applied statistical methods. Three principal projects illustrated the wealth of information gained through the application of statistical data analyses to diverse problems.

  17. Population activity statistics dissect subthreshold and spiking variability in V1.

    Science.gov (United States)

    Bányai, Mihály; Koman, Zsombor; Orbán, Gergő

    2017-07-01

    Response variability, as measured by fluctuating responses upon repeated performance of trials, is a major component of neural responses, and its characterization is key to interpret high dimensional population recordings. Response variability and covariability display predictable changes upon changes in stimulus and cognitive or behavioral state, providing an opportunity to test the predictive power of models of neural variability. Still, there is little agreement on which model to use as a building block for population-level analyses, and models of variability are often treated as a subject of choice. We investigate two competing models, the doubly stochastic Poisson (DSP) model assuming stochasticity at spike generation, and the rectified Gaussian (RG) model tracing variability back to membrane potential variance, to analyze stimulus-dependent modulation of both single-neuron and pairwise response statistics. Using a pair of model neurons, we demonstrate that the two models predict similar single-cell statistics. However, DSP and RG models have contradicting predictions on the joint statistics of spiking responses. To test the models against data, we build a population model to simulate stimulus change-related modulations in pairwise response statistics. We use single-unit data from the primary visual cortex (V1) of monkeys to show that while model predictions for variance are qualitatively similar to experimental data, only the RG model's predictions are compatible with joint statistics. These results suggest that models using Poisson-like variability might fail to capture important properties of response statistics. We argue that membrane potential-level modeling of stochasticity provides an efficient strategy to model correlations. NEW & NOTEWORTHY Neural variability and covariability are puzzling aspects of cortical computations. For efficient decoding and prediction, models of information encoding in neural populations hinge on an appropriate model of

  18. THE ABSOLUTE MAGNITUDE OF RRc VARIABLES FROM STATISTICAL PARALLAX

    International Nuclear Information System (INIS)

    Kollmeier, Juna A.; Burns, Christopher R.; Thompson, Ian B.; Preston, George W.; Crane, Jeffrey D.; Madore, Barry F.; Morrell, Nidia; Prieto, José L.; Shectman, Stephen; Simon, Joshua D.; Villanueva, Edward; Szczygieł, Dorota M.; Gould, Andrew; Sneden, Christopher; Dong, Subo

    2013-01-01

    We present the first definitive measurement of the absolute magnitude of RR Lyrae c-type variable stars (RRc) determined purely from statistical parallax. We use a sample of 242 RRc variables selected from the All Sky Automated Survey for which high-quality light curves, photometry, and proper motions are available. We obtain high-resolution echelle spectra for these objects to determine radial velocities and abundances as part of the Carnegie RR Lyrae Survey. We find that M V,RRc = 0.59 ± 0.10 at a mean metallicity of [Fe/H] = –1.59. This is to be compared with previous estimates for RRab stars (M V,RRab = 0.76 ± 0.12) and the only direct measurement of an RRc absolute magnitude (RZ Cephei, M V,RRc = 0.27 ± 0.17). We find the bulk velocity of the halo relative to the Sun to be (W π , W θ , W z ) = (12.0, –209.9, 3.0) km s –1 in the radial, rotational, and vertical directions with dispersions (σ W π ,σ W θ ,σ W z ) = (150.4, 106.1, 96.0) km s -1 . For the disk, we find (W π , W θ , W z ) = (13.0, –42.0, –27.3) km s –1 relative to the Sun with dispersions (σ W π ,σ W θ ,σ W z ) = (67.7,59.2,54.9) km s -1 . Finally, as a byproduct of our statistical framework, we are able to demonstrate that UCAC2 proper-motion errors are significantly overestimated as verified by UCAC4

  19. A variable thickness window: Thermal and structural analyses

    International Nuclear Information System (INIS)

    Wang, Zhibi; Kuzay, T.M.

    1994-01-01

    In this paper, the finite difference formulations for variable thickness thermal analysis and variable thickness plane stress analysis are presented. In heat transfer analysis, radiation effects and temperature-dependent thermal conductivity are taken into account. While in thermal stress analysis, the thermal expansion coefficient is considered as temperature dependent. An application of the variable thickness window to an Advanced Photon Source beamline is presented

  20. Statistical analyses to support guidelines for marine avian sampling. Final report

    Science.gov (United States)

    Kinlan, Brian P.; Zipkin, Elise; O'Connell, Allan F.; Caldow, Chris

    2012-01-01

    distribution to describe counts of a given species in a particular region and season. 4. Using a large database of historical at-sea seabird survey data, we applied this technique to identify appropriate statistical distributions for modeling a variety of species, allowing the distribution to vary by season. For each species and season, we used the selected distribution to calculate and map retrospective statistical power to detect hotspots and coldspots, and map pvalues from Monte Carlo significance tests of hotspots and coldspots, in discrete lease blocks designated by the U.S. Department of Interior, Bureau of Ocean Energy Management (BOEM). 5. Because our definition of hotspots and coldspots does not explicitly include variability over time, we examine the relationship between the temporal scale of sampling and the proportion of variance captured in time series of key environmental correlates of marine bird abundance, as well as available marine bird abundance time series, and use these analyses to develop recommendations for the temporal distribution of sampling to adequately represent both shortterm and long-term variability. We conclude by presenting a schematic “decision tree” showing how this power analysis approach would fit in a general framework for avian survey design, and discuss implications of model assumptions and results. We discuss avenues for future development of this work, and recommendations for practical implementation in the context of siting and wildlife assessment for offshore renewable energy development projects.

  1. THE ABSOLUTE MAGNITUDE OF RRc VARIABLES FROM STATISTICAL PARALLAX

    Energy Technology Data Exchange (ETDEWEB)

    Kollmeier, Juna A.; Burns, Christopher R.; Thompson, Ian B.; Preston, George W.; Crane, Jeffrey D.; Madore, Barry F.; Morrell, Nidia; Prieto, José L.; Shectman, Stephen; Simon, Joshua D.; Villanueva, Edward [Observatories of the Carnegie Institution of Washington, 813 Santa Barbara Street, Pasadena, CA 91101 (United States); Szczygieł, Dorota M.; Gould, Andrew [Department of Astronomy, The Ohio State University, 4051 McPherson Laboratory, Columbus, OH 43210 (United States); Sneden, Christopher [Department of Astronomy, University of Texas at Austin, TX 78712 (United States); Dong, Subo [Institute for Advanced Study, 500 Einstein Drive, Princeton, NJ 08540 (United States)

    2013-09-20

    We present the first definitive measurement of the absolute magnitude of RR Lyrae c-type variable stars (RRc) determined purely from statistical parallax. We use a sample of 242 RRc variables selected from the All Sky Automated Survey for which high-quality light curves, photometry, and proper motions are available. We obtain high-resolution echelle spectra for these objects to determine radial velocities and abundances as part of the Carnegie RR Lyrae Survey. We find that M{sub V,RRc} = 0.59 ± 0.10 at a mean metallicity of [Fe/H] = –1.59. This is to be compared with previous estimates for RRab stars (M{sub V,RRab} = 0.76 ± 0.12) and the only direct measurement of an RRc absolute magnitude (RZ Cephei, M{sub V,RRc} = 0.27 ± 0.17). We find the bulk velocity of the halo relative to the Sun to be (W{sub π}, W{sub θ}, W{sub z} ) = (12.0, –209.9, 3.0) km s{sup –1} in the radial, rotational, and vertical directions with dispersions (σ{sub W{sub π}},σ{sub W{sub θ}},σ{sub W{sub z}}) = (150.4, 106.1, 96.0) km s{sup -1}. For the disk, we find (W{sub π}, W{sub θ}, W{sub z} ) = (13.0, –42.0, –27.3) km s{sup –1} relative to the Sun with dispersions (σ{sub W{sub π}},σ{sub W{sub θ}},σ{sub W{sub z}}) = (67.7,59.2,54.9) km s{sup -1}. Finally, as a byproduct of our statistical framework, we are able to demonstrate that UCAC2 proper-motion errors are significantly overestimated as verified by UCAC4.

  2. Statistical Analyses of Second Indoor Bio-Release Field Evaluation Study at Idaho National Laboratory

    Energy Technology Data Exchange (ETDEWEB)

    Amidan, Brett G.; Pulsipher, Brent A.; Matzke, Brett D.

    2009-12-17

    number of zeros. Using QQ plots these data characteristics show a lack of normality from the data after contamination. Normality is improved when looking at log(CFU/cm2). Variance component analysis (VCA) and analysis of variance (ANOVA) were used to estimate the amount of variance due to each source and to determine which sources of variability were statistically significant. In general, the sampling methods interacted with the across event variability and with the across room variability. For this reason, it was decided to do analyses for each sampling method, individually. The between event variability and between room variability were significant for each method, except for the between event variability for the swabs. For both the wipes and vacuums, the within room standard deviation was much larger (26.9 for wipes and 7.086 for vacuums) than the between event standard deviation (6.552 for wipes and 1.348 for vacuums) and the between room standard deviation (6.783 for wipes and 1.040 for vacuums). Swabs between room standard deviation was 0.151, while both the within room and between event standard deviations are less than 0.10 (all measurements in CFU/cm2).

  3. Flow prediction models using macroclimatic variables and multivariate statistical techniques in the Cauca River Valley

    International Nuclear Information System (INIS)

    Carvajal Escobar Yesid; Munoz, Flor Matilde

    2007-01-01

    The project this centred in the revision of the state of the art of the ocean-atmospheric phenomena that you affect the Colombian hydrology especially The Phenomenon Enos that causes a socioeconomic impact of first order in our country, it has not been sufficiently studied; therefore it is important to approach the thematic one, including the variable macroclimates associated to the Enos in the analyses of water planning. The analyses include revision of statistical techniques of analysis of consistency of hydrological data with the objective of conforming a database of monthly flow of the river reliable and homogeneous Cauca. Statistical methods are used (Analysis of data multivariante) specifically The analysis of principal components to involve them in the development of models of prediction of flows monthly means in the river Cauca involving the Lineal focus as they are the model autoregressive AR, ARX and Armax and the focus non lineal Net Artificial Network.

  4. Atmospheric forcing of decadal Baltic Sea level variability in the last 200 years. A statistical analysis

    Energy Technology Data Exchange (ETDEWEB)

    Huenicke, B. [GKSS-Forschungszentrum Geesthacht GmbH (Germany). Inst. fuer Kuestenforschung

    2008-11-06

    This study aims at the estimation of the impact of different atmospheric factors on the past sealevel variations (up to 200 years) in the Baltic Sea by statistically analysing the relationship between Baltic Sea level records and observational and proxy-based reconstructed climatic data sets. The focus lies on the identification and possible quantification of the contribution of sealevel pressure (wind), air-temperature and precipitation to the low-frequency (decadal and multi-decadal) variability of Baltic Sea level. It is known that the wind forcing is the main factor explaining average Baltic Sea level variability at inter-annual to decadal timescales, especially in wintertime. In this thesis it is statistically estimated to what extent other regional climate factors contribute to the spatially heterogeneous Baltic Sea level variations around the isostatic trend at multi-decadal timescales. Although the statistical analysis cannot be completely conclusive, as the potential climate drivers are all statistically interrelated to some degree, the results indicate that precipitation should be taken into account as an explanatory variable for sea-level variations. On the one hand it has been detected that the amplitude of the annual cycle of Baltic Sea level has increased throughout the 20th century and precipitation seems to be the only factor among those analysed (wind through SLP field, barometric effect, temperature and precipitation) that can account for this evolution. On the other hand, precipitation increases the ability to hindcast inter-annual variations of sea level in some regions and seasons, especially in the Southern Baltic in summertime. The mechanism by which precipitation exerts its influence on Baltic Sea level is not ascertained in this statistical analysis due to the lack of long salinity time series. This result, however, represents a working hypothesis that can be confirmed or disproved by long simulations of the Baltic Sea system - ocean

  5. Molecular variability analyses of Apple chlorotic leaf spot virus

    Indian Academy of Sciences (India)

    The highest degree of variability was observed in the middle portion with 9 amino acid substitutions in contrast to the N-terminal and C-terminal ends, which were maximally conserved with only 4 amino acid substitutions. In phylogenetic analysis no reasonable correlation between host species and/or geographic origin of ...

  6. SOCR Analyses: Implementation and Demonstration of a New Graphical Statistics Educational Toolkit

    Directory of Open Access Journals (Sweden)

    Annie Chu

    2009-04-01

    Full Text Available The web-based, Java-written SOCR (Statistical Online Computational Resource toolshave been utilized in many undergraduate and graduate level statistics courses for sevenyears now (Dinov 2006; Dinov et al. 2008b. It has been proven that these resourcescan successfully improve students' learning (Dinov et al. 2008b. Being rst publishedonline in 2005, SOCR Analyses is a somewhat new component and it concentrate on datamodeling for both parametric and non-parametric data analyses with graphical modeldiagnostics. One of the main purposes of SOCR Analyses is to facilitate statistical learn-ing for high school and undergraduate students. As we have already implemented SOCRDistributions and Experiments, SOCR Analyses and Charts fulll the rest of a standardstatistics curricula. Currently, there are four core components of SOCR Analyses. Linearmodels included in SOCR Analyses are simple linear regression, multiple linear regression,one-way and two-way ANOVA. Tests for sample comparisons include t-test in the para-metric category. Some examples of SOCR Analyses' in the non-parametric category areWilcoxon rank sum test, Kruskal-Wallis test, Friedman's test, Kolmogorov-Smirno testand Fligner-Killeen test. Hypothesis testing models include contingency table, Friedman'stest and Fisher's exact test. The last component of Analyses is a utility for computingsample sizes for normal distribution. In this article, we present the design framework,computational implementation and the utilization of SOCR Analyses.

  7. Statistical analyses of scatterplots to identify important factors in large-scale simulations, 2: robustness of techniques

    International Nuclear Information System (INIS)

    Kleijnen, J.P.C.; Helton, J.C.

    1999-01-01

    The robustness of procedures for identifying patterns in scatterplots generated in Monte Carlo sensitivity analyses is investigated. These procedures are based on attempts to detect increasingly complex patterns in the scatterplots under consideration and involve the identification of (i) linear relationships with correlation coefficients, (ii) monotonic relationships with rank correlation coefficients, (iii) trends in central tendency as defined by means, medians and the Kruskal-Wallis statistic, (iv) trends in variability as defined by variances and interquartile ranges, and (v) deviations from randomness as defined by the chi-square statistic. The following two topics related to the robustness of these procedures are considered for a sequence of example analyses with a large model for two-phase fluid flow: the presence of Type I and Type II errors, and the stability of results obtained with independent Latin hypercube samples. Observations from analysis include: (i) Type I errors are unavoidable, (ii) Type II errors can occur when inappropriate analysis procedures are used, (iii) physical explanations should always be sought for why statistical procedures identify variables as being important, and (iv) the identification of important variables tends to be stable for independent Latin hypercube samples

  8. Combining epidemiologic and biostatistical tools to enhance variable selection in HIV cohort analyses.

    Directory of Open Access Journals (Sweden)

    Christopher Rentsch

    Full Text Available BACKGROUND: Variable selection is an important step in building a multivariate regression model for which several methods and statistical packages are available. A comprehensive approach for variable selection in complex multivariate regression analyses within HIV cohorts is explored by utilizing both epidemiological and biostatistical procedures. METHODS: Three different methods for variable selection were illustrated in a study comparing survival time between subjects in the Department of Defense's National History Study and the Atlanta Veterans Affairs Medical Center's HIV Atlanta VA Cohort Study. The first two methods were stepwise selection procedures, based either on significance tests (Score test, or on information theory (Akaike Information Criterion, while the third method employed a Bayesian argument (Bayesian Model Averaging. RESULTS: All three methods resulted in a similar parsimonious survival model. Three of the covariates previously used in the multivariate model were not included in the final model suggested by the three approaches. When comparing the parsimonious model to the previously published model, there was evidence of less variance in the main survival estimates. CONCLUSIONS: The variable selection approaches considered in this study allowed building a model based on significance tests, on an information criterion, and on averaging models using their posterior probabilities. A parsimonious model that balanced these three approaches was found to provide a better fit than the previously reported model.

  9. Variables associated with achievement in higher education: A systematic review of meta-analyses.

    Science.gov (United States)

    Schneider, Michael; Preckel, Franzis

    2017-06-01

    The last 2 decades witnessed a surge in empirical studies on the variables associated with achievement in higher education. A number of meta-analyses synthesized these findings. In our systematic literature review, we included 38 meta-analyses investigating 105 correlates of achievement, based on 3,330 effect sizes from almost 2 million students. We provide a list of the 105 variables, ordered by the effect size, and summary statistics for central research topics. The results highlight the close relation between social interaction in courses and achievement. Achievement is also strongly associated with the stimulation of meaningful learning by presenting information in a clear way, relating it to the students, and using conceptually demanding learning tasks. Instruction and communication technology has comparably weak effect sizes, which did not increase over time. Strong moderator effects are found for almost all instructional methods, indicating that how a method is implemented in detail strongly affects achievement. Teachers with high-achieving students invest time and effort in designing the microstructure of their courses, establish clear learning goals, and employ feedback practices. This emphasizes the importance of teacher training in higher education. Students with high achievement are characterized by high self-efficacy, high prior achievement and intelligence, conscientiousness, and the goal-directed use of learning strategies. Barring the paucity of controlled experiments and the lack of meta-analyses on recent educational innovations, the variables associated with achievement in higher education are generally well investigated and well understood. By using these findings, teachers, university administrators, and policymakers can increase the effectivity of higher education. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  10. CADDIS Volume 4. Data Analysis: Advanced Analyses - Controlling for Natural Variability

    Science.gov (United States)

    Methods for controlling natural variability, predicting environmental conditions from biological observations method, biological trait data, species sensitivity distributions, propensity scores, Advanced Analyses of Data Analysis references.

  11. CADDIS Volume 4. Data Analysis: Advanced Analyses - Controlling for Natural Variability: SSD Plot Diagrams

    Science.gov (United States)

    Methods for controlling natural variability, predicting environmental conditions from biological observations method, biological trait data, species sensitivity distributions, propensity scores, Advanced Analyses of Data Analysis references.

  12. Scalar statistics in variable property turbulent channel flows

    NARCIS (Netherlands)

    Patel, A.; Boersma, B.J.; Pecnik, R.

    2017-01-01

    Direct numerical simulation of fully developed, internally heated channel flows with isothermal walls is performed using the low-Mach-number approximation of Navier-Stokes equation to investigate the influence of temperature-dependent properties on turbulent scalar statistics. Different constitutive

  13. Finite-sample instrumental variables Inference using an Asymptotically Pivotal Statistic

    NARCIS (Netherlands)

    Bekker, P.; Kleibergen, F.R.

    2001-01-01

    The paper considers the K-statistic, Kleibergen’s (2000) adaptation ofthe Anderson-Rubin (AR) statistic in instrumental variables regression.Compared to the AR-statistic this K-statistic shows improvedasymptotic efficiency in terms of degrees of freedom in overidentifiedmodels and yet it shares,

  14. Finite-sample instrumental variables inference using an asymptotically pivotal statistic

    NARCIS (Netherlands)

    Bekker, Paul A.; Kleibergen, Frank

    2001-01-01

    The paper considers the K-statistic, Kleibergen’s (2000) adaptation of the Anderson-Rubin (AR) statistic in instrumental variables regression. Compared to the AR-statistic this K-statistic shows improved asymptotic efficiency in terms of degrees of freedom in overidenti?ed models and yet it shares,

  15. Homeostasis and Gauss statistics: barriers to understanding natural variability.

    Science.gov (United States)

    West, Bruce J

    2010-06-01

    In this paper, the concept of knowledge is argued to be the top of a three-tiered system of science. The first tier is that of measurement and data, followed by information consisting of the patterns within the data, and ending with theory that interprets the patterns and yields knowledge. Thus, when a scientific theory ceases to be consistent with the database the knowledge based on that theory must be re-examined and potentially modified. Consequently, all knowledge, like glory, is transient. Herein we focus on the non-normal statistics of physiologic time series and conclude that the empirical inverse power-law statistics and long-time correlations are inconsistent with the theoretical notion of homeostasis. We suggest replacing the notion of homeostasis with that of Fractal Physiology.

  16. Scripts for TRUMP data analyses. Part II (HLA-related data): statistical analyses specific for hematopoietic stem cell transplantation.

    Science.gov (United States)

    Kanda, Junya

    2016-01-01

    The Transplant Registry Unified Management Program (TRUMP) made it possible for members of the Japan Society for Hematopoietic Cell Transplantation (JSHCT) to analyze large sets of national registry data on autologous and allogeneic hematopoietic stem cell transplantation. However, as the processes used to collect transplantation information are complex and differed over time, the background of these processes should be understood when using TRUMP data. Previously, information on the HLA locus of patients and donors had been collected using a questionnaire-based free-description method, resulting in some input errors. To correct minor but significant errors and provide accurate HLA matching data, the use of a Stata or EZR/R script offered by the JSHCT is strongly recommended when analyzing HLA data in the TRUMP dataset. The HLA mismatch direction, mismatch counting method, and different impacts of HLA mismatches by stem cell source are other important factors in the analysis of HLA data. Additionally, researchers should understand the statistical analyses specific for hematopoietic stem cell transplantation, such as competing risk, landmark analysis, and time-dependent analysis, to correctly analyze transplant data. The data center of the JSHCT can be contacted if statistical assistance is required.

  17. SOCR Analyses - an Instructional Java Web-based Statistical Analysis Toolkit.

    Science.gov (United States)

    Chu, Annie; Cui, Jenny; Dinov, Ivo D

    2009-03-01

    The Statistical Online Computational Resource (SOCR) designs web-based tools for educational use in a variety of undergraduate courses (Dinov 2006). Several studies have demonstrated that these resources significantly improve students' motivation and learning experiences (Dinov et al. 2008). SOCR Analyses is a new component that concentrates on data modeling and analysis using parametric and non-parametric techniques supported with graphical model diagnostics. Currently implemented analyses include commonly used models in undergraduate statistics courses like linear models (Simple Linear Regression, Multiple Linear Regression, One-Way and Two-Way ANOVA). In addition, we implemented tests for sample comparisons, such as t-test in the parametric category; and Wilcoxon rank sum test, Kruskal-Wallis test, Friedman's test, in the non-parametric category. SOCR Analyses also include several hypothesis test models, such as Contingency tables, Friedman's test and Fisher's exact test.The code itself is open source (http://socr.googlecode.com/), hoping to contribute to the efforts of the statistical computing community. The code includes functionality for each specific analysis model and it has general utilities that can be applied in various statistical computing tasks. For example, concrete methods with API (Application Programming Interface) have been implemented in statistical summary, least square solutions of general linear models, rank calculations, etc. HTML interfaces, tutorials, source code, activities, and data are freely available via the web (www.SOCR.ucla.edu). Code examples for developers and demos for educators are provided on the SOCR Wiki website.In this article, the pedagogical utilization of the SOCR Analyses is discussed, as well as the underlying design framework. As the SOCR project is on-going and more functions and tools are being added to it, these resources are constantly improved. The reader is strongly encouraged to check the SOCR site for most

  18. Methods in pharmacoepidemiology: a review of statistical analyses and data reporting in pediatric drug utilization studies.

    Science.gov (United States)

    Sequi, Marco; Campi, Rita; Clavenna, Antonio; Bonati, Maurizio

    2013-03-01

    To evaluate the quality of data reporting and statistical methods performed in drug utilization studies in the pediatric population. Drug utilization studies evaluating all drug prescriptions to children and adolescents published between January 1994 and December 2011 were retrieved and analyzed. For each study, information on measures of exposure/consumption, the covariates considered, descriptive and inferential analyses, statistical tests, and methods of data reporting was extracted. An overall quality score was created for each study using a 12-item checklist that took into account the presence of outcome measures, covariates of measures, descriptive measures, statistical tests, and graphical representation. A total of 22 studies were reviewed and analyzed. Of these, 20 studies reported at least one descriptive measure. The mean was the most commonly used measure (18 studies), but only five of these also reported the standard deviation. Statistical analyses were performed in 12 studies, with the chi-square test being the most commonly performed test. Graphs were presented in 14 papers. Sixteen papers reported the number of drug prescriptions and/or packages, and ten reported the prevalence of the drug prescription. The mean quality score was 8 (median 9). Only seven of the 22 studies received a score of ≥10, while four studies received a score of statistical methods and reported data in a satisfactory manner. We therefore conclude that the methodology of drug utilization studies needs to be improved.

  19. Assessing compositional variability through graphical analysis and Bayesian statistical approaches: case studies on transgenic crops.

    Science.gov (United States)

    Harrigan, George G; Harrison, Jay M

    2012-01-01

    New transgenic (GM) crops are subjected to extensive safety assessments that include compositional comparisons with conventional counterparts as a cornerstone of the process. The influence of germplasm, location, environment, and agronomic treatments on compositional variability is, however, often obscured in these pair-wise comparisons. Furthermore, classical statistical significance testing can often provide an incomplete and over-simplified summary of highly responsive variables such as crop composition. In order to more clearly describe the influence of the numerous sources of compositional variation we present an introduction to two alternative but complementary approaches to data analysis and interpretation. These include i) exploratory data analysis (EDA) with its emphasis on visualization and graphics-based approaches and ii) Bayesian statistical methodology that provides easily interpretable and meaningful evaluations of data in terms of probability distributions. The EDA case-studies include analyses of herbicide-tolerant GM soybean and insect-protected GM maize and soybean. Bayesian approaches are presented in an analysis of herbicide-tolerant GM soybean. Advantages of these approaches over classical frequentist significance testing include the more direct interpretation of results in terms of probabilities pertaining to quantities of interest and no confusion over the application of corrections for multiple comparisons. It is concluded that a standardized framework for these methodologies could provide specific advantages through enhanced clarity of presentation and interpretation in comparative assessments of crop composition.

  20. Finite-sample instrumental variables inference using an asymptotically pivotal statistic

    NARCIS (Netherlands)

    Bekker, P; Kleibergen, F

    2003-01-01

    We consider the K-statistic, Kleibergen's (2002, Econometrica 70, 1781-1803) adaptation of the Anderson-Rubin (AR) statistic in instrumental variables regression. Whereas Kleibergen (2002) especially analyzes the asymptotic behavior of the statistic, we focus on finite-sample properties in, a

  1. Repeatability of heart rate variability in congenital hypothyroidism as analysed by detrended fluctuation analysis

    International Nuclear Information System (INIS)

    Echeverría, J C; Solís, L I; Pérez, J E; Gaitán, M J; Mandujano, M; Sánchez, M C; González-Camarena, R; Rivera, I R

    2009-01-01

    The analysis of heart rate fluctuations, or heart rate variability (HRV), may be applied to explore children's neurodevelopment. However, previous studies have reported poor reliability (repeatability) of HRV measures in children at rest and during light exercise. Whether the reliability can be improved by controlling variables such as physical activity, breathing rate and tidal volume, or by selecting non-conventional techniques for analysing the data remains as an open question. We evaluated the short-term repeatability of RR-interval data from medicated children with congenital hypothyroidism (CH). The α 1 exponents, obtained by detrended fluctuation analysis (DFA), from the data of 21 children collected at two different sessions were compared. Elapsed days between sessions were 59 ± 33, and data were obtained during 10 min, trying to restrict the children's activity while being seated. We found statistical agreement between the means of α 1 exponents for each session (p = 0.94) and no bias with a low-coefficient variation (9.1%); an intraclass correlation coefficient ri = 0.48 ([0.14 0.72], 95% confidence interval) was also estimated. These findings, which were compared with results obtained by conventional time and frequency techniques, indicate the existence of agreement between the α 1 exponents obtained at each session, thereby providing support concerning the repeatability of HRV data as analysed by DFA in children with congenital hypothyroidism. Of particular interest was also the agreement found by using the central frequency of the high-frequency band and the parameter pNN20, both showing better or similar ri than α 1 (0.77 [0.57 0.89] and 0.51 [0.17 0.74], respectively), yet considerably better repeatability than other conventional time and frequency parameters

  2. Statistical methods for analysing the relationship between bank profitability and liquidity

    OpenAIRE

    Boguslaw Guzik

    2006-01-01

    The article analyses the most popular methods for the empirical estimation of the relationship between bank profitability and liquidity. Owing to the fact that profitability depends on various factors (both economic and non-economic), a simple correlation coefficient, two-dimensional (profitability/liquidity) graphs or models where profitability depends only on liquidity variable do not provide good and reliable results. Quite good results can be obtained only when multifactorial profitabilit...

  3. Statistical analyses in the study of solar wind-magnetosphere coupling

    International Nuclear Information System (INIS)

    Baker, D.N.

    1985-01-01

    Statistical analyses provide a valuable method for establishing initially the existence (or lack of existence) of a relationship between diverse data sets. Statistical methods also allow one to make quantitative assessments of the strengths of observed relationships. This paper reviews the essential techniques and underlying statistical bases for the use of correlative methods in solar wind-magnetosphere coupling studies. Techniques of visual correlation and time-lagged linear cross-correlation analysis are emphasized, but methods of multiple regression, superposed epoch analysis, and linear prediction filtering are also described briefly. The long history of correlation analysis in the area of solar wind-magnetosphere coupling is reviewed with the assessments organized according to data averaging time scales (minutes to years). It is concluded that these statistical methods can be very useful first steps, but that case studies and various advanced analysis methods should be employed to understand fully the average response of the magnetosphere to solar wind input. It is clear that many workers have not always recognized underlying assumptions of statistical methods and thus the significance of correlation results can be in doubt. Long-term averages (greater than or equal to 1 hour) can reveal gross relationships, but only when dealing with high-resolution data (1 to 10 min) can one reach conclusions pertinent to magnetospheric response time scales and substorm onset mechanisms

  4. Economic Statistical Design of Variable Sampling Interval X¯$\\overline X $ Control Chart Based on Surrogate Variable Using Genetic Algorithms

    Directory of Open Access Journals (Sweden)

    Lee Tae-Hoon

    2016-12-01

    Full Text Available In many cases, a X¯$\\overline X $ control chart based on a performance variable is used in industrial fields. Typically, the control chart monitors the measurements of a performance variable itself. However, if the performance variable is too costly or impossible to measure, and a less expensive surrogate variable is available, the process may be more efficiently controlled using surrogate variables. In this paper, we present a model for the economic statistical design of a VSI (Variable Sampling Interval X¯$\\overline X $ control chart using a surrogate variable that is linearly correlated with the performance variable. We derive the total average profit model from an economic viewpoint and apply the model to a Very High Temperature Reactor (VHTR nuclear fuel measurement system and derive the optimal result using genetic algorithms. Compared with the control chart based on a performance variable, the proposed model gives a larger expected net income per unit of time in the long-run if the correlation between the performance variable and the surrogate variable is relatively high. The proposed model was confined to the sample mean control chart under the assumption that a single assignable cause occurs according to the Poisson process. However, the model may also be extended to other types of control charts using a single or multiple assignable cause assumptions such as VSS (Variable Sample Size X¯$\\overline X $ control chart, EWMA, CUSUM charts and so on.

  5. Exploratory study on a statistical method to analyse time resolved data obtained during nanomaterial exposure measurements

    International Nuclear Information System (INIS)

    Clerc, F; Njiki-Menga, G-H; Witschger, O

    2013-01-01

    Most of the measurement strategies that are suggested at the international level to assess workplace exposure to nanomaterials rely on devices measuring, in real time, airborne particles concentrations (according different metrics). Since none of the instruments to measure aerosols can distinguish a particle of interest to the background aerosol, the statistical analysis of time resolved data requires special attention. So far, very few approaches have been used for statistical analysis in the literature. This ranges from simple qualitative analysis of graphs to the implementation of more complex statistical models. To date, there is still no consensus on a particular approach and the current period is always looking for an appropriate and robust method. In this context, this exploratory study investigates a statistical method to analyse time resolved data based on a Bayesian probabilistic approach. To investigate and illustrate the use of the this statistical method, particle number concentration data from a workplace study that investigated the potential for exposure via inhalation from cleanout operations by sandpapering of a reactor producing nanocomposite thin films have been used. In this workplace study, the background issue has been addressed through the near-field and far-field approaches and several size integrated and time resolved devices have been used. The analysis of the results presented here focuses only on data obtained with two handheld condensation particle counters. While one was measuring at the source of the released particles, the other one was measuring in parallel far-field. The Bayesian probabilistic approach allows a probabilistic modelling of data series, and the observed task is modelled in the form of probability distributions. The probability distributions issuing from time resolved data obtained at the source can be compared with the probability distributions issuing from the time resolved data obtained far-field, leading in a

  6. Statistical analyses of the data on occupational radiation expousure at JPDR

    International Nuclear Information System (INIS)

    Kato, Shohei; Anazawa, Yutaka; Matsuno, Kenji; Furuta, Toshishiro; Akiyama, Isamu

    1980-01-01

    In the statistical analyses of the data on occupational radiation exposure at JPDR, statistical features were obtained as follows. (1) The individual doses followed log-normal distribution. (2) In the distribution of doses from one job in controlled area, the logarithm of the mean (μ) depended on the exposure rate (γ(mR/h)), and the σ correlated to the nature of the job and normally distributed. These relations were as follows. μ = 0.48 ln r-0.24, σ = 1.2 +- 0.58 (3) For the data containing different groups, the distribution of doses showed a polygonal line on the log-normal probability paper. (4) Under the dose limitation, the distribution of the doses showed asymptotic curve along the limit on the log-normal probability paper. (author)

  7. arXiv Statistical Analyses of Higgs- and Z-Portal Dark Matter Models

    CERN Document Server

    Ellis, John; Marzola, Luca; Raidal, Martti

    2018-06-12

    We perform frequentist and Bayesian statistical analyses of Higgs- and Z-portal models of dark matter particles with spin 0, 1/2 and 1. Our analyses incorporate data from direct detection and indirect detection experiments, as well as LHC searches for monojet and monophoton events, and we also analyze the potential impacts of future direct detection experiments. We find acceptable regions of the parameter spaces for Higgs-portal models with real scalar, neutral vector, Majorana or Dirac fermion dark matter particles, and Z-portal models with Majorana or Dirac fermion dark matter particles. In many of these cases, there are interesting prospects for discovering dark matter particles in Higgs or Z decays, as well as dark matter particles weighing $\\gtrsim 100$ GeV. Negative results from planned direct detection experiments would still allow acceptable regions for Higgs- and Z-portal models with Majorana or Dirac fermion dark matter particles.

  8. The Use of Statistical Process Control Tools for Analysing Financial Statements

    Directory of Open Access Journals (Sweden)

    Niezgoda Janusz

    2017-06-01

    Full Text Available This article presents the proposed application of one type of the modified Shewhart control charts in the monitoring of changes in the aggregated level of financial ratios. The control chart x̅ has been used as a basis of analysis. The examined variable from the sample in the mentioned chart is the arithmetic mean. The author proposes to substitute it with a synthetic measure that is determined and based on the selected ratios. As the ratios mentioned above, are expressed in different units and characters, the author applies standardisation. The results of selected comparative analyses have been presented for both bankrupts and non-bankrupts. They indicate the possibility of using control charts as an auxiliary tool in financial analyses.

  9. Characteristics of electrostatic solitary waves observed in the plasma sheet boundary: Statistical analyses

    Directory of Open Access Journals (Sweden)

    H. Kojima

    1999-01-01

    Full Text Available We present the characteristics of the Electrostatic Solitary Waves (ESW observed by the Geotail spacecraft in the plasma sheet boundary layer based on the statistical analyses. We also discuss the results referring to a model of ESW generation due to electron beams, which is proposed by computer simulations. In this generation model, the nonlinear evolution of Langmuir waves excited by electron bump-on-tail instabilities leads to formation of isolated electrostatic potential structures corresponding to "electron hole" in the phase space. The statistical analyses of the Geotail data, which we conducted under the assumption that polarity of ESW potentials is positive, show that most of ESW propagate in the same direction of electron beams, which are observed by the plasma instrument, simultaneously. Further, we also find that the ESW potential energy is much smaller than the background electron thermal energy and that the ESW potential widths are typically shorter than 60 times of local electron Debye length when we assume that the ESW potentials travel in the same velocity of electron beams. These results are very consistent with the ESW generation model that the nonlinear evolution of electron bump-on-tail instability leads to the formation of electron holes in the phase space.

  10. Spatio-temporal dependencies between hospital beds, physicians and health expenditure using visual variables and data classification in statistical table

    Science.gov (United States)

    Medyńska-Gulij, Beata; Cybulski, Paweł

    2016-06-01

    This paper analyses the use of table visual variables of statistical data of hospital beds as an important tool for revealing spatio-temporal dependencies. It is argued that some of conclusions from the data about public health and public expenditure on health have a spatio-temporal reference. Different from previous studies, this article adopts combination of cartographic pragmatics and spatial visualization with previous conclusions made in public health literature. While the significant conclusions about health care and economic factors has been highlighted in research papers, this article is the first to apply visual analysis to statistical table together with maps which is called previsualisation.

  11. Spatio-temporal dependencies between hospital beds, physicians and health expenditure using visual variables and data classification in statistical table

    Directory of Open Access Journals (Sweden)

    Medyńska-Gulij Beata

    2016-06-01

    Full Text Available This paper analyses the use of table visual variables of statistical data of hospital beds as an important tool for revealing spatio-temporal dependencies. It is argued that some of conclusions from the data about public health and public expenditure on health have a spatio-temporal reference. Different from previous studies, this article adopts combination of cartographic pragmatics and spatial visualization with previous conclusions made in public health literature. While the significant conclusions about health care and economic factors has been highlighted in research papers, this article is the first to apply visual analysis to statistical table together with maps which is called previsualisation.

  12. Visualization of the variability of 3D statistical shape models by animation.

    Science.gov (United States)

    Lamecker, Hans; Seebass, Martin; Lange, Thomas; Hege, Hans-Christian; Deuflhard, Peter

    2004-01-01

    Models of the 3D shape of anatomical objects and the knowledge about their statistical variability are of great benefit in many computer assisted medical applications like images analysis, therapy or surgery planning. Statistical model of shapes have successfully been applied to automate the task of image segmentation. The generation of 3D statistical shape models requires the identification of corresponding points on two shapes. This remains a difficult problem, especially for shapes of complicated topology. In order to interpret and validate variations encoded in a statistical shape model, visual inspection is of great importance. This work describes the generation and interpretation of statistical shape models of the liver and the pelvic bone.

  13. A weighted U-statistic for genetic association analyses of sequencing data.

    Science.gov (United States)

    Wei, Changshuai; Li, Ming; He, Zihuai; Vsevolozhskaya, Olga; Schaid, Daniel J; Lu, Qing

    2014-12-01

    With advancements in next-generation sequencing technology, a massive amount of sequencing data is generated, which offers a great opportunity to comprehensively investigate the role of rare variants in the genetic etiology of complex diseases. Nevertheless, the high-dimensional sequencing data poses a great challenge for statistical analysis. The association analyses based on traditional statistical methods suffer substantial power loss because of the low frequency of genetic variants and the extremely high dimensionality of the data. We developed a Weighted U Sequencing test, referred to as WU-SEQ, for the high-dimensional association analysis of sequencing data. Based on a nonparametric U-statistic, WU-SEQ makes no assumption of the underlying disease model and phenotype distribution, and can be applied to a variety of phenotypes. Through simulation studies and an empirical study, we showed that WU-SEQ outperformed a commonly used sequence kernel association test (SKAT) method when the underlying assumptions were violated (e.g., the phenotype followed a heavy-tailed distribution). Even when the assumptions were satisfied, WU-SEQ still attained comparable performance to SKAT. Finally, we applied WU-SEQ to sequencing data from the Dallas Heart Study (DHS), and detected an association between ANGPTL 4 and very low density lipoprotein cholesterol. © 2014 WILEY PERIODICALS, INC.

  14. Statistical parameters of random heterogeneity estimated by analysing coda waves based on finite difference method

    Science.gov (United States)

    Emoto, K.; Saito, T.; Shiomi, K.

    2017-12-01

    Short-period (2 s) seismograms. We found that the energy of the coda of long-period seismograms shows a spatially flat distribution. This phenomenon is well known in short-period seismograms and results from the scattering by small-scale heterogeneities. We estimate the statistical parameters that characterize the small-scale random heterogeneity by modelling the spatiotemporal energy distribution of long-period seismograms. We analyse three moderate-size earthquakes that occurred in southwest Japan. We calculate the spatial distribution of the energy density recorded by a dense seismograph network in Japan at the period bands of 8-16 s, 4-8 s and 2-4 s and model them by using 3-D finite difference (FD) simulations. Compared to conventional methods based on statistical theories, we can calculate more realistic synthetics by using the FD simulation. It is not necessary to assume a uniform background velocity, body or surface waves and scattering properties considered in general scattering theories. By taking the ratio of the energy of the coda area to that of the entire area, we can separately estimate the scattering and the intrinsic absorption effects. Our result reveals the spectrum of the random inhomogeneity in a wide wavenumber range including the intensity around the corner wavenumber as P(m) = 8πε2a3/(1 + a2m2)2, where ε = 0.05 and a = 3.1 km, even though past studies analysing higher-frequency records could not detect the corner. Finally, we estimate the intrinsic attenuation by modelling the decay rate of the energy. The method proposed in this study is suitable for quantifying the statistical properties of long-wavelength subsurface random inhomogeneity, which leads the way to characterizing a wider wavenumber range of spectra, including the corner wavenumber.

  15. Statistical analyses of digital collections: Using a large corpus of systematic reviews to study non-citations

    DEFF Research Database (Denmark)

    Frandsen, Tove Faber; Nicolaisen, Jeppe

    2017-01-01

    Using statistical methods to analyse digital material for patterns makes it possible to detect patterns in big data that we would otherwise not be able to detect. This paper seeks to exemplify this fact by statistically analysing a large corpus of references in systematic reviews. The aim...

  16. Systematic Mapping and Statistical Analyses of Valley Landform and Vegetation Asymmetries Across Hydroclimatic Gradients

    Science.gov (United States)

    Poulos, M. J.; Pierce, J. L.; McNamara, J. P.; Flores, A. N.; Benner, S. G.

    2015-12-01

    Terrain aspect alters the spatial distribution of insolation across topography, driving eco-pedo-hydro-geomorphic feedbacks that can alter landform evolution and result in valley asymmetries for a suite of land surface characteristics (e.g. slope length and steepness, vegetation, soil properties, and drainage development). Asymmetric valleys serve as natural laboratories for studying how landscapes respond to climate perturbation. In the semi-arid montane granodioritic terrain of the Idaho batholith, Northern Rocky Mountains, USA, prior works indicate that reduced insolation on northern (pole-facing) aspects prolongs snow pack persistence, and is associated with thicker, finer-grained soils, that retain more water, prolong the growing season, support coniferous forest rather than sagebrush steppe ecosystems, stabilize slopes at steeper angles, and produce sparser drainage networks. We hypothesize that the primary drivers of valley asymmetry development are changes in the pedon-scale water-balance that coalesce to alter catchment-scale runoff and drainage development, and ultimately cause the divide between north and south-facing land surfaces to migrate northward. We explore this conceptual framework by coupling land surface analyses with statistical modeling to assess relationships and the relative importance of land surface characteristics. Throughout the Idaho batholith, we systematically mapped and tabulated various statistical measures of landforms, land cover, and hydroclimate within discrete valley segments (n=~10,000). We developed a random forest based statistical model to predict valley slope asymmetry based upon numerous measures (n>300) of landscape asymmetries. Preliminary results suggest that drainages are tightly coupled with hillslopes throughout the region, with drainage-network slope being one of the strongest predictors of land-surface-averaged slope asymmetry. When slope-related statistics are excluded, due to possible autocorrelation, valley

  17. Statistical Significance of the Contribution of Variables to the PCA Solution: An Alternative Permutation Strategy

    Science.gov (United States)

    Linting, Marielle; van Os, Bart Jan; Meulman, Jacqueline J.

    2011-01-01

    In this paper, the statistical significance of the contribution of variables to the principal components in principal components analysis (PCA) is assessed nonparametrically by the use of permutation tests. We compare a new strategy to a strategy used in previous research consisting of permuting the columns (variables) of a data matrix…

  18. Comparative Analysis of Upper Ocean Heat Content Variability from Ensemble Operational Ocean Analyses

    Science.gov (United States)

    Xue, Yan; Balmaseda, Magdalena A.; Boyer, Tim; Ferry, Nicolas; Good, Simon; Ishikawa, Ichiro; Rienecker, Michele; Rosati, Tony; Yin, Yonghong; Kumar, Arun

    2012-01-01

    Upper ocean heat content (HC) is one of the key indicators of climate variability on many time-scales extending from seasonal to interannual to long-term climate trends. For example, HC in the tropical Pacific provides information on thermocline anomalies that is critical for the longlead forecast skill of ENSO. Since HC variability is also associated with SST variability, a better understanding and monitoring of HC variability can help us understand and forecast SST variability associated with ENSO and other modes such as Indian Ocean Dipole (IOD), Pacific Decadal Oscillation (PDO), Tropical Atlantic Variability (TAV) and Atlantic Multidecadal Oscillation (AMO). An accurate ocean initialization of HC anomalies in coupled climate models could also contribute to skill in decadal climate prediction. Errors, and/or uncertainties, in the estimation of HC variability can be affected by many factors including uncertainties in surface forcings, ocean model biases, and deficiencies in data assimilation schemes. Changes in observing systems can also leave an imprint on the estimated variability. The availability of multiple operational ocean analyses (ORA) that are routinely produced by operational and research centers around the world provides an opportunity to assess uncertainties in HC analyses, to help identify gaps in observing systems as they impact the quality of ORAs and therefore climate model forecasts. A comparison of ORAs also gives an opportunity to identify deficiencies in data assimilation schemes, and can be used as a basis for development of real-time multi-model ensemble HC monitoring products. The OceanObs09 Conference called for an intercomparison of ORAs and use of ORAs for global ocean monitoring. As a follow up, we intercompared HC variations from ten ORAs -- two objective analyses based on in-situ data only and eight model analyses based on ocean data assimilation systems. The mean, annual cycle, interannual variability and longterm trend of HC have

  19. Statistical contact angle analyses; "slow moving" drops on a horizontal silicon-oxide surface.

    Science.gov (United States)

    Schmitt, M; Grub, J; Heib, F

    2015-06-01

    Sessile drop experiments on horizontal surfaces are commonly used to characterise surface properties in science and in industry. The advancing angle and the receding angle are measurable on every solid. Specially on horizontal surfaces even the notions themselves are critically questioned by some authors. Building a standard, reproducible and valid method of measuring and defining specific (advancing/receding) contact angles is an important challenge of surface science. Recently we have developed two/three approaches, by sigmoid fitting, by independent and by dependent statistical analyses, which are practicable for the determination of specific angles/slopes if inclining the sample surface. These approaches lead to contact angle data which are independent on "user-skills" and subjectivity of the operator which is also of urgent need to evaluate dynamic measurements of contact angles. We will show in this contribution that the slightly modified procedures are also applicable to find specific angles for experiments on horizontal surfaces. As an example droplets on a flat freshly cleaned silicon-oxide surface (wafer) are dynamically measured by sessile drop technique while the volume of the liquid is increased/decreased. The triple points, the time, the contact angles during the advancing and the receding of the drop obtained by high-precision drop shape analysis are statistically analysed. As stated in the previous contribution the procedure is called "slow movement" analysis due to the small covered distance and the dominance of data points with low velocity. Even smallest variations in velocity such as the minimal advancing motion during the withdrawing of the liquid are identifiable which confirms the flatness and the chemical homogeneity of the sample surface and the high sensitivity of the presented approaches. Copyright © 2014 Elsevier Inc. All rights reserved.

  20. Statistical analyses of incidents on onshore gas transmission pipelines based on PHMSA database

    International Nuclear Information System (INIS)

    Lam, Chio; Zhou, Wenxing

    2016-01-01

    This article reports statistical analyses of the mileage and pipe-related incidents data corresponding to the onshore gas transmission pipelines in the US between 2002 and 2013 collected by the Pipeline Hazardous Material Safety Administration of the US Department of Transportation. The analysis indicates that there are approximately 480,000 km of gas transmission pipelines in the US, approximately 60% of them more than 45 years old as of 2013. Eighty percent of the pipelines are Class 1 pipelines, and about 20% of the pipelines are Classes 2 and 3 pipelines. It is found that the third-party excavation, external corrosion, material failure and internal corrosion are the four leading failure causes, responsible for more than 75% of the total incidents. The 12-year average rate of rupture equals 3.1 × 10"−"5 per km-year due to all failure causes combined. External corrosion is the leading cause for ruptures: the 12-year average rupture rate due to external corrosion equals 1.0 × 10"−"5 per km-year and is twice the rupture rate due to the third-party excavation or material failure. The study provides insights into the current state of gas transmission pipelines in the US and baseline failure statistics for the quantitative risk assessments of such pipelines. - Highlights: • Analyze PHMSA pipeline mileage and incident data between 2002 and 2013. • Focus on gas transmission pipelines. • Leading causes for pipeline failures are identified. • Provide baseline failure statistics for risk assessments of gas transmission pipelines.

  1. [Hydrologic variability and sensitivity based on Hurst coefficient and Bartels statistic].

    Science.gov (United States)

    Lei, Xu; Xie, Ping; Wu, Zi Yi; Sang, Yan Fang; Zhao, Jiang Yan; Li, Bin Bin

    2018-04-01

    Due to the global climate change and frequent human activities in recent years, the pure stochastic components of hydrological sequence is mixed with one or several of the variation ingredients, including jump, trend, period and dependency. It is urgently needed to clarify which indices should be used to quantify the degree of their variability. In this study, we defined the hydrological variability based on Hurst coefficient and Bartels statistic, and used Monte Carlo statistical tests to test and analyze their sensitivity to different variants. When the hydrological sequence had jump or trend variation, both Hurst coefficient and Bartels statistic could reflect the variation, with the Hurst coefficient being more sensitive to weak jump or trend variation. When the sequence had period, only the Bartels statistic could detect the mutation of the sequence. When the sequence had a dependency, both the Hurst coefficient and the Bartels statistics could reflect the variation, with the latter could detect weaker dependent variations. For the four variations, both the Hurst variability and Bartels variability increased with the increases of variation range. Thus, they could be used to measure the variation intensity of the hydrological sequence. We analyzed the temperature series of different weather stations in the Lancang River basin. Results showed that the temperature of all stations showed the upward trend or jump, indicating that the entire basin had experienced warming in recent years and the temperature variability in the upper and lower reaches was much higher. This case study showed the practicability of the proposed method.

  2. Best Statistical Distribution of flood variables for Johor River in Malaysia

    Science.gov (United States)

    Salarpour Goodarzi, M.; Yusop, Z.; Yusof, F.

    2012-12-01

    A complex flood event is always characterized by a few characteristics such as flood peak, flood volume, and flood duration, which might be mutually correlated. This study explored the statistical distribution of peakflow, flood duration and flood volume at Rantau Panjang gauging station on the Johor River in Malaysia. Hourly data were recorded for 45 years. The data were analysed based on water year (July - June). Five distributions namely, Log Normal, Generalize Pareto, Log Pearson, Normal and Generalize Extreme Value (GEV) were used to model the distribution of all the three variables. Anderson-Darling and Kolmogorov-Smirnov goodness-of-fit tests were used to evaluate the best fit. Goodness-of-fit tests at 5% level of significance indicate that all the models can be used to model the distribution of peakflow, flood duration and flood volume. However, Generalize Pareto distribution is found to be the most suitable model when tested with the Anderson-Darling test and the, Kolmogorov-Smirnov suggested that GEV is the best for peakflow. The result of this research can be used to improve flood frequency analysis. Comparison between Generalized Extreme Value, Generalized Pareto and Log Pearson distributions in the Cumulative Distribution Function of peakflow

  3. Chemometric and Statistical Analyses of ToF-SIMS Spectra of Increasingly Complex Biological Samples

    Energy Technology Data Exchange (ETDEWEB)

    Berman, E S; Wu, L; Fortson, S L; Nelson, D O; Kulp, K S; Wu, K J

    2007-10-24

    Characterizing and classifying molecular variation within biological samples is critical for determining fundamental mechanisms of biological processes that will lead to new insights including improved disease understanding. Towards these ends, time-of-flight secondary ion mass spectrometry (ToF-SIMS) was used to examine increasingly complex samples of biological relevance, including monosaccharide isomers, pure proteins, complex protein mixtures, and mouse embryo tissues. The complex mass spectral data sets produced were analyzed using five common statistical and chemometric multivariate analysis techniques: principal component analysis (PCA), linear discriminant analysis (LDA), partial least squares discriminant analysis (PLSDA), soft independent modeling of class analogy (SIMCA), and decision tree analysis by recursive partitioning. PCA was found to be a valuable first step in multivariate analysis, providing insight both into the relative groupings of samples and into the molecular basis for those groupings. For the monosaccharides, pure proteins and protein mixture samples, all of LDA, PLSDA, and SIMCA were found to produce excellent classification given a sufficient number of compound variables calculated. For the mouse embryo tissues, however, SIMCA did not produce as accurate a classification. The decision tree analysis was found to be the least successful for all the data sets, providing neither as accurate a classification nor chemical insight for any of the tested samples. Based on these results we conclude that as the complexity of the sample increases, so must the sophistication of the multivariate technique used to classify the samples. PCA is a preferred first step for understanding ToF-SIMS data that can be followed by either LDA or PLSDA for effective classification analysis. This study demonstrates the strength of ToF-SIMS combined with multivariate statistical and chemometric techniques to classify increasingly complex biological samples

  4. Curve fitting and modeling with splines using statistical variable selection techniques

    Science.gov (United States)

    Smith, P. L.

    1982-01-01

    The successful application of statistical variable selection techniques to fit splines is demonstrated. Major emphasis is given to knot selection, but order determination is also discussed. Two FORTRAN backward elimination programs, using the B-spline basis, were developed. The program for knot elimination is compared in detail with two other spline-fitting methods and several statistical software packages. An example is also given for the two-variable case using a tensor product basis, with a theoretical discussion of the difficulties of their use.

  5. The relationship between venture capital investment and macro economic variables via statistical computation method

    Science.gov (United States)

    Aygunes, Gunes

    2017-07-01

    The objective of this paper is to survey and determine the macroeconomic factors affecting the level of venture capital (VC) investments in a country. The literary depends on venture capitalists' quality and countries' venture capital investments. The aim of this paper is to give relationship between venture capital investment and macro economic variables via statistical computation method. We investigate the countries and macro economic variables. By using statistical computation method, we derive correlation between venture capital investments and macro economic variables. According to method of logistic regression model (logit regression or logit model), macro economic variables are correlated with each other in three group. Venture capitalists regard correlations as a indicator. Finally, we give correlation matrix of our results.

  6. Municipal solid waste composition: Sampling methodology, statistical analyses, and case study evaluation

    International Nuclear Information System (INIS)

    Edjabou, Maklawe Essonanawe; Jensen, Morten Bang; Götze, Ramona; Pivnenko, Kostyantyn; Petersen, Claus; Scheutz, Charlotte; Astrup, Thomas Fruergaard

    2015-01-01

    Highlights: • Tiered approach to waste sorting ensures flexibility and facilitates comparison of solid waste composition data. • Food and miscellaneous wastes are the main fractions contributing to the residual household waste. • Separation of food packaging from food leftovers during sorting is not critical for determination of the solid waste composition. - Abstract: Sound waste management and optimisation of resource recovery require reliable data on solid waste generation and composition. In the absence of standardised and commonly accepted waste characterisation methodologies, various approaches have been reported in literature. This limits both comparability and applicability of the results. In this study, a waste sampling and sorting methodology for efficient and statistically robust characterisation of solid waste was introduced. The methodology was applied to residual waste collected from 1442 households distributed among 10 individual sub-areas in three Danish municipalities (both single and multi-family house areas). In total 17 tonnes of waste were sorted into 10–50 waste fractions, organised according to a three-level (tiered approach) facilitating comparison of the waste data between individual sub-areas with different fractionation (waste from one municipality was sorted at “Level III”, e.g. detailed, while the two others were sorted only at “Level I”). The results showed that residual household waste mainly contained food waste (42 ± 5%, mass per wet basis) and miscellaneous combustibles (18 ± 3%, mass per wet basis). The residual household waste generation rate in the study areas was 3–4 kg per person per week. Statistical analyses revealed that the waste composition was independent of variations in the waste generation rate. Both, waste composition and waste generation rates were statistically similar for each of the three municipalities. While the waste generation rates were similar for each of the two housing types (single

  7. Municipal solid waste composition: Sampling methodology, statistical analyses, and case study evaluation

    Energy Technology Data Exchange (ETDEWEB)

    Edjabou, Maklawe Essonanawe, E-mail: vine@env.dtu.dk [Department of Environmental Engineering, Technical University of Denmark, 2800 Kgs. Lyngby (Denmark); Jensen, Morten Bang; Götze, Ramona; Pivnenko, Kostyantyn [Department of Environmental Engineering, Technical University of Denmark, 2800 Kgs. Lyngby (Denmark); Petersen, Claus [Econet AS, Omøgade 8, 2.sal, 2100 Copenhagen (Denmark); Scheutz, Charlotte; Astrup, Thomas Fruergaard [Department of Environmental Engineering, Technical University of Denmark, 2800 Kgs. Lyngby (Denmark)

    2015-02-15

    Highlights: • Tiered approach to waste sorting ensures flexibility and facilitates comparison of solid waste composition data. • Food and miscellaneous wastes are the main fractions contributing to the residual household waste. • Separation of food packaging from food leftovers during sorting is not critical for determination of the solid waste composition. - Abstract: Sound waste management and optimisation of resource recovery require reliable data on solid waste generation and composition. In the absence of standardised and commonly accepted waste characterisation methodologies, various approaches have been reported in literature. This limits both comparability and applicability of the results. In this study, a waste sampling and sorting methodology for efficient and statistically robust characterisation of solid waste was introduced. The methodology was applied to residual waste collected from 1442 households distributed among 10 individual sub-areas in three Danish municipalities (both single and multi-family house areas). In total 17 tonnes of waste were sorted into 10–50 waste fractions, organised according to a three-level (tiered approach) facilitating comparison of the waste data between individual sub-areas with different fractionation (waste from one municipality was sorted at “Level III”, e.g. detailed, while the two others were sorted only at “Level I”). The results showed that residual household waste mainly contained food waste (42 ± 5%, mass per wet basis) and miscellaneous combustibles (18 ± 3%, mass per wet basis). The residual household waste generation rate in the study areas was 3–4 kg per person per week. Statistical analyses revealed that the waste composition was independent of variations in the waste generation rate. Both, waste composition and waste generation rates were statistically similar for each of the three municipalities. While the waste generation rates were similar for each of the two housing types (single

  8. Testing Genetic Pleiotropy with GWAS Summary Statistics for Marginal and Conditional Analyses.

    Science.gov (United States)

    Deng, Yangqing; Pan, Wei

    2017-12-01

    There is growing interest in testing genetic pleiotropy, which is when a single genetic variant influences multiple traits. Several methods have been proposed; however, these methods have some limitations. First, all the proposed methods are based on the use of individual-level genotype and phenotype data; in contrast, for logistical, and other, reasons, summary statistics of univariate SNP-trait associations are typically only available based on meta- or mega-analyzed large genome-wide association study (GWAS) data. Second, existing tests are based on marginal pleiotropy, which cannot distinguish between direct and indirect associations of a single genetic variant with multiple traits due to correlations among the traits. Hence, it is useful to consider conditional analysis, in which a subset of traits is adjusted for another subset of traits. For example, in spite of substantial lowering of low-density lipoprotein cholesterol (LDL) with statin therapy, some patients still maintain high residual cardiovascular risk, and, for these patients, it might be helpful to reduce their triglyceride (TG) level. For this purpose, in order to identify new therapeutic targets, it would be useful to identify genetic variants with pleiotropic effects on LDL and TG after adjusting the latter for LDL; otherwise, a pleiotropic effect of a genetic variant detected by a marginal model could simply be due to its association with LDL only, given the well-known correlation between the two types of lipids. Here, we develop a new pleiotropy testing procedure based only on GWAS summary statistics that can be applied for both marginal analysis and conditional analysis. Although the main technical development is based on published union-intersection testing methods, care is needed in specifying conditional models to avoid invalid statistical estimation and inference. In addition to the previously used likelihood ratio test, we also propose using generalized estimating equations under the

  9. Detailed statistical contact angle analyses; "slow moving" drops on inclining silicon-oxide surfaces.

    Science.gov (United States)

    Schmitt, M; Groß, K; Grub, J; Heib, F

    2015-06-01

    Contact angle determination by sessile drop technique is essential to characterise surface properties in science and in industry. Different specific angles can be observed on every solid which are correlated with the advancing or the receding of the triple line. Different procedures and definitions for the determination of specific angles exist which are often not comprehensible or reproducible. Therefore one of the most important things in this area is to build standard, reproducible and valid methods for determining advancing/receding contact angles. This contribution introduces novel techniques to analyse dynamic contact angle measurements (sessile drop) in detail which are applicable for axisymmetric and non-axisymmetric drops. Not only the recently presented fit solution by sigmoid function and the independent analysis of the different parameters (inclination, contact angle, velocity of the triple point) but also the dependent analysis will be firstly explained in detail. These approaches lead to contact angle data and different access on specific contact angles which are independent from "user-skills" and subjectivity of the operator. As example the motion behaviour of droplets on flat silicon-oxide surfaces after different surface treatments is dynamically measured by sessile drop technique when inclining the sample plate. The triple points, the inclination angles, the downhill (advancing motion) and the uphill angles (receding motion) obtained by high-precision drop shape analysis are independently and dependently statistically analysed. Due to the small covered distance for the dependent analysis (contact angle determination. They are characterised by small deviations of the computed values. Additional to the detailed introduction of this novel analytical approaches plus fit solution special motion relations for the drop on inclined surfaces and detailed relations about the reactivity of the freshly cleaned silicon wafer surface resulting in acceleration

  10. Dispensing processes impact apparent biological activity as determined by computational and statistical analyses.

    Directory of Open Access Journals (Sweden)

    Sean Ekins

    Full Text Available Dispensing and dilution processes may profoundly influence estimates of biological activity of compounds. Published data show Ephrin type-B receptor 4 IC50 values obtained via tip-based serial dilution and dispensing versus acoustic dispensing with direct dilution differ by orders of magnitude with no correlation or ranking of datasets. We generated computational 3D pharmacophores based on data derived by both acoustic and tip-based transfer. The computed pharmacophores differ significantly depending upon dispensing and dilution methods. The acoustic dispensing-derived pharmacophore correctly identified active compounds in a subsequent test set where the tip-based method failed. Data from acoustic dispensing generates a pharmacophore containing two hydrophobic features, one hydrogen bond donor and one hydrogen bond acceptor. This is consistent with X-ray crystallography studies of ligand-protein interactions and automatically generated pharmacophores derived from this structural data. In contrast, the tip-based data suggest a pharmacophore with two hydrogen bond acceptors, one hydrogen bond donor and no hydrophobic features. This pharmacophore is inconsistent with the X-ray crystallographic studies and automatically generated pharmacophores. In short, traditional dispensing processes are another important source of error in high-throughput screening that impacts computational and statistical analyses. These findings have far-reaching implications in biological research.

  11. Computational Performance Optimisation for Statistical Analysis of the Effect of Nano-CMOS Variability on Integrated Circuits

    Directory of Open Access Journals (Sweden)

    Zheng Xie

    2013-01-01

    Full Text Available The intrinsic variability of nanoscale VLSI technology must be taken into account when analyzing circuit designs to predict likely yield. Monte-Carlo- (MC- and quasi-MC- (QMC- based statistical techniques do this by analysing many randomised or quasirandomised copies of circuits. The randomisation must model forms of variability that occur in nano-CMOS technology, including “atomistic” effects without intradie correlation and effects with intradie correlation between neighbouring devices. A major problem is the computational cost of carrying out sufficient analyses to produce statistically reliable results. The use of principal components analysis, behavioural modeling, and an implementation of “Statistical Blockade” (SB is shown to be capable of achieving significant reduction in the computational costs. A computation time reduction of 98.7% was achieved for a commonly used asynchronous circuit element. Replacing MC by QMC analysis can achieve further computation reduction, and this is illustrated for more complex circuits, with the results being compared with those of transistor-level simulations. The “yield prediction” analysis of SRAM arrays is taken as a case study, where the arrays contain up to 1536 transistors modelled using parameters appropriate to 35 nm technology. It is reported that savings of up to 99.85% in computation time were obtained.

  12. Statistical methods and regression analysis of stratospheric ozone and meteorological variables in Isfahan

    Science.gov (United States)

    Hassanzadeh, S.; Hosseinibalam, F.; Omidvari, M.

    2008-04-01

    Data of seven meteorological variables (relative humidity, wet temperature, dry temperature, maximum temperature, minimum temperature, ground temperature and sun radiation time) and ozone values have been used for statistical analysis. Meteorological variables and ozone values were analyzed using both multiple linear regression and principal component methods. Data for the period 1999-2004 are analyzed jointly using both methods. For all periods, temperature dependent variables were highly correlated, but were all negatively correlated with relative humidity. Multiple regression analysis was used to fit the meteorological variables using the meteorological variables as predictors. A variable selection method based on high loading of varimax rotated principal components was used to obtain subsets of the predictor variables to be included in the linear regression model of the meteorological variables. In 1999, 2001 and 2002 one of the meteorological variables was weakly influenced predominantly by the ozone concentrations. However, the model did not predict that the meteorological variables for the year 2000 were not influenced predominantly by the ozone concentrations that point to variation in sun radiation. This could be due to other factors that were not explicitly considered in this study.

  13. Comparison of climate envelope models developed using expert-selected variables versus statistical selection

    Science.gov (United States)

    Brandt, Laura A.; Benscoter, Allison; Harvey, Rebecca G.; Speroterra, Carolina; Bucklin, David N.; Romañach, Stephanie; Watling, James I.; Mazzotti, Frank J.

    2017-01-01

    Climate envelope models are widely used to describe potential future distribution of species under different climate change scenarios. It is broadly recognized that there are both strengths and limitations to using climate envelope models and that outcomes are sensitive to initial assumptions, inputs, and modeling methods Selection of predictor variables, a central step in modeling, is one of the areas where different techniques can yield varying results. Selection of climate variables to use as predictors is often done using statistical approaches that develop correlations between occurrences and climate data. These approaches have received criticism in that they rely on the statistical properties of the data rather than directly incorporating biological information about species responses to temperature and precipitation. We evaluated and compared models and prediction maps for 15 threatened or endangered species in Florida based on two variable selection techniques: expert opinion and a statistical method. We compared model performance between these two approaches for contemporary predictions, and the spatial correlation, spatial overlap and area predicted for contemporary and future climate predictions. In general, experts identified more variables as being important than the statistical method and there was low overlap in the variable sets (0.9 for area under the curve (AUC) and >0.7 for true skill statistic (TSS). Spatial overlap, which compares the spatial configuration between maps constructed using the different variable selection techniques, was only moderate overall (about 60%), with a great deal of variability across species. Difference in spatial overlap was even greater under future climate projections, indicating additional divergence of model outputs from different variable selection techniques. Our work is in agreement with other studies which have found that for broad-scale species distribution modeling, using statistical methods of variable

  14. Using Statistical Process Control Charts to Study Stuttering Frequency Variability during a Single Day

    Science.gov (United States)

    Karimi, Hamid; O'Brian, Sue; Onslow, Mark; Jones, Mark; Menzies, Ross; Packman, Ann

    2013-01-01

    Purpose: Stuttering varies between and within speaking situations. In this study, the authors used statistical process control charts with 10 case studies to investigate variability of stuttering frequency. Method: Participants were 10 adults who stutter. The authors counted the percentage of syllables stuttered (%SS) for segments of their speech…

  15. Authigenic oxide Neodymium Isotopic composition as a proxy of seawater: applying multivariate statistical analyses.

    Science.gov (United States)

    McKinley, C. C.; Scudder, R.; Thomas, D. J.

    2016-12-01

    The Neodymium Isotopic composition (Nd IC) of oxide coatings has been applied as a tracer of water mass composition and used to address fundamental questions about past ocean conditions. The leached authigenic oxide coating from marine sediment is widely assumed to reflect the dissolved trace metal composition of the bottom water interacting with sediment at the seafloor. However, recent studies have shown that readily reducible sediment components, in addition to trace metal fluxes from the pore water, are incorporated into the bottom water, influencing the trace metal composition of leached oxide coatings. This challenges the prevailing application of the authigenic oxide Nd IC as a proxy of seawater composition. Therefore, it is important to identify the component end-members that create sediments of different lithology and determine if, or how they might contribute to the Nd IC of oxide coatings. To investigate lithologic influence on the results of sequential leaching, we selected two sites with complete bulk sediment statistical characterization. Site U1370 in the South Pacific Gyre, is predominantly composed of Rhyolite ( 60%) and has a distinguishable ( 10%) Fe-Mn Oxyhydroxide component (Dunlea et al., 2015). Site 1149 near the Izu-Bonin-Arc is predominantly composed of dispersed ash ( 20-50%) and eolian dust from Asia ( 50-80%) (Scudder et al., 2014). We perform a two-step leaching procedure: a 14 mL of 0.02 M hydroxylamine hydrochloride (HH) in 20% acetic acid buffered to a pH 4 for one hour, targeting metals bound to Fe- and Mn- oxides fractions, and a second HH leach for 12 hours, designed to remove any remaining oxides from the residual component. We analyze all three resulting fractions for a large suite of major, trace and rare earth elements, a sub-set of the samples are also analyzed for Nd IC. We use multivariate statistical analyses of the resulting geochemical data to identify how each component of the sediment partitions across the sequential

  16. Review of Statistical Analyses Resulting from Performance of HLDWD-DWPF-005

    International Nuclear Information System (INIS)

    Beck, R.S.

    1997-01-01

    The Engineering Department at the Defense Waste Processing Facility (DWPF) has reviewed two reports from the Statistical Consulting Section (SCS) involving the statistical analysis of test results for analysis of small sample inserts (references 1 ampersand 2). The test results cover two proposed analytical methods, a room temperature hydrofluoric acid preparation (Cold Chem) and a sodium peroxide/sodium hydroxide fusion modified for insert samples (Modified Fusion). The reports support implementation of the proposed small sample containers and analytical methods at DWPF. Hydragard sampler valve performance was typical of previous results (reference 3). Using an element from each major feed stream. lithium from the frit and iron from the sludge, the sampler was determined to deliver a uniform mixture in either sample container.The lithium to iron ratios were equivalent for the standard 15 ml vial and the 3 ml insert.The proposed method provide equivalent analyses as compared to the current methods. The biases associated with the proposed methods on a vitrified basis are less than 5% for major elements. The sum of oxides for the proposed method compares favorably with the sum of oxides for the conventional methods. However, the average sum of oxides for the Cold Chem method was 94.3% which is below the minimum required recovery of 95%. Both proposed methods, cold Chem and Modified Fusion, will be required at first to provide an accurate analysis which will routinely meet the 95% and 105% average sum of oxides limit for Product Composition Control System (PCCS).Issued to be resolved during phased implementation are as follows: (1) Determine calcine/vitrification factor for radioactive feed; (2) Evaluate covariance matrix change against process operating ranges to determine optimum sample size; (3) Evaluate sources for low sum of oxides; and (4) Improve remote operability of production versions of equipment and instruments for installation in 221-S.The specifics of

  17. ZnO crystals obtained by electrodeposition: Statistical analysis of most important process variables

    International Nuclear Information System (INIS)

    Cembrero, Jesus; Busquets-Mataix, David

    2009-01-01

    In this paper a comparative study by means of a statistical analysis of the main process variables affecting ZnO crystal electrodeposition is presented. ZnO crystals were deposited on two different substrates, silicon wafer and indium tin oxide. The control variables were substrate types, electrolyte concentration, temperature, exposition time and current density. The morphologies of the different substrates were observed using scanning electron microscopy. The percentage of substrate area covered by ZnO deposit was calculated by computational image analysis. The design of the applied experiments was based on a two-level factorial analysis involving a series of 32 experiments and an analysis of variance. Statistical results reveal that variables exerting a significant influence on the area covered by ZnO deposit are electrolyte concentration, substrate type and time of deposition, together with a combined two-factor interaction between temperature and current density. However, morphology is also influenced by surface roughness of the substrates

  18. Correlating tephras and cryptotephras using glass compositional analyses and numerical and statistical methods: Review and evaluation

    Science.gov (United States)

    Lowe, David J.; Pearce, Nicholas J. G.; Jorgensen, Murray A.; Kuehn, Stephen C.; Tryon, Christian A.; Hayward, Chris L.

    2017-11-01

    We define tephras and cryptotephras and their components (mainly ash-sized particles of glass ± crystals in distal deposits) and summarize the basis of tephrochronology as a chronostratigraphic correlational and dating tool for palaeoenvironmental, geological, and archaeological research. We then document and appraise recent advances in analytical methods used to determine the major, minor, and trace elements of individual glass shards from tephra or cryptotephra deposits to aid their correlation and application. Protocols developed recently for the electron probe microanalysis of major elements in individual glass shards help to improve data quality and standardize reporting procedures. A narrow electron beam (diameter ∼3-5 μm) can now be used to analyze smaller glass shards than previously attainable. Reliable analyses of 'microshards' (defined here as glass shards T2 test). Randomization tests can be used where distributional assumptions such as multivariate normality underlying parametric tests are doubtful. Compositional data may be transformed and scaled before being subjected to multivariate statistical procedures including calculation of distance matrices, hierarchical cluster analysis, and PCA. Such transformations may make the assumption of multivariate normality more appropriate. A sequential procedure using Mahalanobis distance and the Hotelling two-sample T2 test is illustrated using glass major element data from trachytic to phonolitic Kenyan tephras. All these methods require a broad range of high-quality compositional data which can be used to compare 'unknowns' with reference (training) sets that are sufficiently complete to account for all possible correlatives, including tephras with heterogeneous glasses that contain multiple compositional groups. Currently, incomplete databases are tending to limit correlation efficacy. The development of an open, online global database to facilitate progress towards integrated, high

  19. Reporting characteristics of meta-analyses in orthodontics: methodological assessment and statistical recommendations.

    Science.gov (United States)

    Papageorgiou, Spyridon N; Papadopoulos, Moschos A; Athanasiou, Athanasios E

    2014-02-01

    Ideally meta-analyses (MAs) should consolidate the characteristics of orthodontic research in order to produce an evidence-based answer. However severe flaws are frequently observed in most of them. The aim of this study was to evaluate the statistical methods, the methodology, and the quality characteristics of orthodontic MAs and to assess their reporting quality during the last years. Electronic databases were searched for MAs (with or without a proper systematic review) in the field of orthodontics, indexed up to 2011. The AMSTAR tool was used for quality assessment of the included articles. Data were analyzed with Student's t-test, one-way ANOVA, and generalized linear modelling. Risk ratios with 95% confidence intervals were calculated to represent changes during the years in reporting of key items associated with quality. A total of 80 MAs with 1086 primary studies were included in this evaluation. Using the AMSTAR tool, 25 (27.3%) of the MAs were found to be of low quality, 37 (46.3%) of medium quality, and 18 (22.5%) of high quality. Specific characteristics like explicit protocol definition, extensive searches, and quality assessment of included trials were associated with a higher AMSTAR score. Model selection and dealing with heterogeneity or publication bias were often problematic in the identified reviews. The number of published orthodontic MAs is constantly increasing, while their overall quality is considered to range from low to medium. Although the number of MAs of medium and high level seems lately to rise, several other aspects need improvement to increase their overall quality.

  20. Statistical Analyses of High-Resolution Aircraft and Satellite Observations of Sea Ice: Applications for Improving Model Simulations

    Science.gov (United States)

    Farrell, S. L.; Kurtz, N. T.; Richter-Menge, J.; Harbeck, J. P.; Onana, V.

    2012-12-01

    Satellite-derived estimates of ice thickness and observations of ice extent over the last decade point to a downward trend in the basin-scale ice volume of the Arctic Ocean. This loss has broad-ranging impacts on the regional climate and ecosystems, as well as implications for regional infrastructure, marine navigation, national security, and resource exploration. New observational datasets at small spatial and temporal scales are now required to improve our understanding of physical processes occurring within the ice pack and advance parameterizations in the next generation of numerical sea-ice models. High-resolution airborne and satellite observations of the sea ice are now available at meter-scale resolution or better that provide new details on the properties and morphology of the ice pack across basin scales. For example the NASA IceBridge airborne campaign routinely surveys the sea ice of the Arctic and Southern Oceans with an advanced sensor suite including laser and radar altimeters and digital cameras that together provide high-resolution measurements of sea ice freeboard, thickness, snow depth and lead distribution. Here we present statistical analyses of the ice pack primarily derived from the following IceBridge instruments: the Digital Mapping System (DMS), a nadir-looking, high-resolution digital camera; the Airborne Topographic Mapper, a scanning lidar; and the University of Kansas snow radar, a novel instrument designed to estimate snow depth on sea ice. Together these instruments provide data from which a wide range of sea ice properties may be derived. We provide statistics on lead distribution and spacing, lead width and area, floe size and distance between floes, as well as ridge height, frequency and distribution. The goals of this study are to (i) identify unique statistics that can be used to describe the characteristics of specific ice regions, for example first-year/multi-year ice, diffuse ice edge/consolidated ice pack, and convergent

  1. Bounding the conservatism in flaw-related variables for pressure vessel integrity analyses

    International Nuclear Information System (INIS)

    Foulds, J.R.; Kennedy, E.L.

    1993-01-01

    The fracture mechanics-based integrity analysis of a pressure vessel, whether performed deterministically or probabilistically, requires use of one or more flaw-related input variables, such as flaw size, number of flaws, flaw location, and flaw type. The specific values of these variables are generally selected with the intent to ensure conservative predictions of vessel integrity. These selected values, however, are largely independent of vessel-specific inspection results, or are, at best, deduced by ''conservative'' interpretation of vessel-specific inspection results without adequate consideration of the pertinent inspection system performance (reliability). In either case, the conservatism associated with the flaw-related variables chosen for analysis remains examination (NDE) technology and the recently formulated ASME Code procedures for qualifying NDE system capability and performance (as applied to selected nuclear power plant components) now provides a systematic means of bounding the conservatism in flaw-related input variables for pressure vessel integrity analyses. This is essentially achieved by establishing probabilistic (risk)-based limits on the assigned variable values, dependent upon the vessel inspection results and on the inspection system unreliability. Described herein is this probabilistic method and its potential application to: (i) defining a vessel-specific ''reference'' flaw for calculating pressure-temperature limit curves in the deterministic evaluation of pressurized water reactor (PWR) reactor vessels, and (ii) limiting the flaw distribution input to a PWR reactor vessel-specific, probabilistic integrity analysis for pressurized thermal shock loads

  2. Variability analysis of AGN: a review of results using new statistical criteria

    Science.gov (United States)

    Zibecchi, L.; Andruchow, I.; Cellone, S. A.; Romero, G. E.; Combi, J. A.

    We present here a re-analysis of the variability results of a sample of active galactic nuclei (AGN), which have been observed on several sessions with the 2.15 m "Jorge Sahade" telescope (CASLEO), San Juan, Argentina, and whose results are published (Romero et al. 1999, 2000, 2002; Cellone et al. 2000). The motivation for this new analysis is the implementation, dur- ing the last years, of improvements in the statistical criteria applied, taking quantitatively into account the incidence of the photometric errors (Cellone et al. 2007). This work is framed as a first step in an integral study on the statistical estimators of AGN variability. This study is motivated by the great diversity of statistical tests that have been proposed to analyze the variability of these objects. Since we note that, in some cases, the results of the object variability depend on the test used, we attempt to make a com- parative study of the various tests and analyze, under the given conditions, which of them is the most efficient and reliable.

  3. Supermathematics and its applications in statistical physics Grassmann variables and the method of supersymmetry

    CERN Document Server

    Wegner, Franz

    2016-01-01

    This text presents the mathematical concepts of Grassmann variables and the method of supersymmetry to a broad audience of physicists interested in applying these tools to disordered and critical systems, as well as related topics in statistical physics. Based on many courses and seminars held by the author, one of the pioneers in this field, the reader is given a systematic and tutorial introduction to the subject matter. The algebra and analysis of Grassmann variables is presented in part I. The mathematics of these variables is applied to a random matrix model, path integrals for fermions, dimer models and the Ising model in two dimensions. Supermathematics - the use of commuting and anticommuting variables on an equal footing - is the subject of part II. The properties of supervectors and supermatrices, which contain both commuting and Grassmann components, are treated in great detail, including the derivation of integral theorems. In part III, supersymmetric physical models are considered. While supersym...

  4. Essentials of Excel, Excel VBA, SAS and Minitab for statistical and financial analyses

    CERN Document Server

    Lee, Cheng-Few; Chang, Jow-Ran; Tai, Tzu

    2016-01-01

    This introductory textbook for business statistics teaches statistical analysis and research methods via business case studies and financial data using Excel, MINITAB, and SAS. Every chapter in this textbook engages the reader with data of individual stock, stock indices, options, and futures. One studies and uses statistics to learn how to study, analyze, and understand a data set of particular interest. Some of the more popular statistical programs that have been developed to use statistical and computational methods to analyze data sets are SAS, SPSS, and MINITAB. Of those, we look at MINITAB and SAS in this textbook. One of the main reasons to use MINITAB is that it is the easiest to use among the popular statistical programs. We look at SAS because it is the leading statistical package used in industry. We also utilize the much less costly and ubiquitous Microsoft Excel to do statistical analysis, as the benefits of Excel have become widely recognized in the academic world and its analytical capabilities...

  5. Analysis of Norwegian bio energy statistics. Quality improvement proposals; Analyse av norsk bioenergistatistikk. Forslag til kvalitetsheving

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2011-07-01

    This report is an assessment of the current model and presentation form of bio energy statistics. It appears proposed revision and enhancement of both collection and data representation. In the context of market development both in general for energy and particularly for bio energy and government targets, a good bio energy statistics form the basis to follow up the objectives and means.(eb)

  6. Statistical power of intervention analyses: simulation and empirical application to treated lumber prices

    Science.gov (United States)

    Jeffrey P. Prestemon

    2009-01-01

    Timber product markets are subject to large shocks deriving from natural disturbances and policy shifts. Statistical modeling of shocks is often done to assess their economic importance. In this article, I simulate the statistical power of univariate and bivariate methods of shock detection using time series intervention models. Simulations show that bivariate methods...

  7. Empirical Correction to the Likelihood Ratio Statistic for Structural Equation Modeling with Many Variables.

    Science.gov (United States)

    Yuan, Ke-Hai; Tian, Yubin; Yanagihara, Hirokazu

    2015-06-01

    Survey data typically contain many variables. Structural equation modeling (SEM) is commonly used in analyzing such data. The most widely used statistic for evaluating the adequacy of a SEM model is T ML, a slight modification to the likelihood ratio statistic. Under normality assumption, T ML approximately follows a chi-square distribution when the number of observations (N) is large and the number of items or variables (p) is small. However, in practice, p can be rather large while N is always limited due to not having enough participants. Even with a relatively large N, empirical results show that T ML rejects the correct model too often when p is not too small. Various corrections to T ML have been proposed, but they are mostly heuristic. Following the principle of the Bartlett correction, this paper proposes an empirical approach to correct T ML so that the mean of the resulting statistic approximately equals the degrees of freedom of the nominal chi-square distribution. Results show that empirically corrected statistics follow the nominal chi-square distribution much more closely than previously proposed corrections to T ML, and they control type I errors reasonably well whenever N ≥ max(50,2p). The formulations of the empirically corrected statistics are further used to predict type I errors of T ML as reported in the literature, and they perform well.

  8. The determinants of bond angle variability in protein/peptide backbones: A comprehensive statistical/quantum mechanics analysis.

    Science.gov (United States)

    Improta, Roberto; Vitagliano, Luigi; Esposito, Luciana

    2015-11-01

    The elucidation of the mutual influence between peptide bond geometry and local conformation has important implications for protein structure refinement, validation, and prediction. To gain insights into the structural determinants and the energetic contributions associated with protein/peptide backbone plasticity, we here report an extensive analysis of the variability of the peptide bond angles by combining statistical analyses of protein structures and quantum mechanics calculations on small model peptide systems. Our analyses demonstrate that all the backbone bond angles strongly depend on the peptide conformation and unveil the existence of regular trends as function of ψ and/or φ. The excellent agreement of the quantum mechanics calculations with the statistical surveys of protein structures validates the computational scheme here employed and demonstrates that the valence geometry of protein/peptide backbone is primarily dictated by local interactions. Notably, for the first time we show that the position of the H(α) hydrogen atom, which is an important parameter in NMR structural studies, is also dependent on the local conformation. Most of the trends observed may be satisfactorily explained by invoking steric repulsive interactions; in some specific cases the valence bond variability is also influenced by hydrogen-bond like interactions. Moreover, we can provide a reliable estimate of the energies involved in the interplay between geometry and conformations. © 2015 Wiley Periodicals, Inc.

  9. A guide to statistical analysis in microbial ecology: a community-focused, living review of multivariate data analyses

    OpenAIRE

    Buttigieg, Pier Luigi; Ramette, Alban Nicolas

    2014-01-01

    The application of multivariate statistical analyses has become a consistent feature in microbial ecology. However, many microbial ecologists are still in the process of developing a deep understanding of these methods and appreciating their limitations. As a consequence, staying abreast of progress and debate in this arena poses an additional challenge to many microbial ecologists. To address these issues, we present the GUide to STatistical Analysis in Microbial Ecology (GUSTA ME): a dynami...

  10. An MGF-based unified framework to determine the joint statistics of partial sums of ordered random variables

    KAUST Repository

    Nam, Sungsik; Alouini, Mohamed-Slim; Yang, Hongchuan

    2010-01-01

    Order statistics find applications in various areas of communications and signal processing. In this paper, we introduce an unified analytical framework to determine the joint statistics of partial sums of ordered random variables (RVs

  11. Rainfall Downscaling Conditional on Upper-air Variables: Assessing Rainfall Statistics in a Changing Climate

    Science.gov (United States)

    Langousis, Andreas; Deidda, Roberto; Marrocu, Marino; Kaleris, Vassilios

    2014-05-01

    Due to its intermittent and highly variable character, and the modeling parameterizations used, precipitation is one of the least well reproduced hydrologic variables by both Global Climate Models (GCMs) and Regional Climate Models (RCMs). This is especially the case at a regional level (where hydrologic risks are assessed) and at small temporal scales (e.g. daily) used to run hydrologic models. In an effort to remedy those shortcomings and assess the effect of climate change on rainfall statistics at hydrologically relevant scales, Langousis and Kaleris (2013) developed a statistical framework for simulation of daily rainfall intensities conditional on upper air variables. The developed downscaling scheme was tested using atmospheric data from the ERA-Interim archive (http://www.ecmwf.int/research/era/do/get/index), and daily rainfall measurements from western Greece, and was proved capable of reproducing several statistical properties of actual rainfall records, at both annual and seasonal levels. This was done solely by conditioning rainfall simulation on a vector of atmospheric predictors, properly selected to reflect the relative influence of upper-air variables on ground-level rainfall statistics. In this study, we apply the developed framework for conditional rainfall simulation using atmospheric data from different GCM/RCM combinations. This is done using atmospheric data from the ENSEMBLES project (http://ensembleseu.metoffice.com), and daily rainfall measurements for an intermediate-sized catchment in Italy; i.e. the Flumendosa catchment. Since GCM/RCM products are suited to reproduce the local climatology in a statistical sense (i.e. in terms of relative frequencies), rather than ensuring a one-to-one temporal correspondence between observed and simulated fields (i.e. as is the case for ERA-interim reanalysis data), we proceed in three steps: a) we use statistical tools to establish a linkage between ERA-Interim upper-air atmospheric forecasts and

  12. Statistical analysis of corn yields responding to climate variability at various spatio-temporal resolutions

    Science.gov (United States)

    Jiang, H.; Lin, T.

    2017-12-01

    Rain-fed corn production systems are subject to sub-seasonal variations of precipitation and temperature during the growing season. As each growth phase has varied inherent physiological process, plants necessitate different optimal environmental conditions during each phase. However, this temporal heterogeneity towards climate variability alongside the lifecycle of crops is often simplified and fixed as constant responses in large scale statistical modeling analysis. To capture the time-variant growing requirements in large scale statistical analysis, we develop and compare statistical models at various spatial and temporal resolutions to quantify the relationship between corn yield and weather factors for 12 corn belt states from 1981 to 2016. The study compares three spatial resolutions (county, agricultural district, and state scale) and three temporal resolutions (crop growth phase, monthly, and growing season) to characterize the effects of spatial and temporal variability. Our results show that the agricultural district model together with growth phase resolution can explain 52% variations of corn yield caused by temperature and precipitation variability. It provides a practical model structure balancing the overfitting problem in county specific model and weak explanation power in state specific model. In US corn belt, precipitation has positive impact on corn yield in growing season except for vegetative stage while extreme heat attains highest sensitivity from silking to dough phase. The results show the northern counties in corn belt area are less interfered by extreme heat but are more vulnerable to water deficiency.

  13. Statistical learning from nonrecurrent experience with discrete input variables and recursive-error-minimization equations

    Science.gov (United States)

    Carter, Jeffrey R.; Simon, Wayne E.

    1990-08-01

    Neural networks are trained using Recursive Error Minimization (REM) equations to perform statistical classification. Using REM equations with continuous input variables reduces the required number of training experiences by factors of one to two orders of magnitude over standard back propagation. Replacing the continuous input variables with discrete binary representations reduces the number of connections by a factor proportional to the number of variables reducing the required number of experiences by another order of magnitude. Undesirable effects of using recurrent experience to train neural networks for statistical classification problems are demonstrated and nonrecurrent experience used to avoid these undesirable effects. 1. THE 1-41 PROBLEM The statistical classification problem which we address is is that of assigning points in ddimensional space to one of two classes. The first class has a covariance matrix of I (the identity matrix) the covariance matrix of the second class is 41. For this reason the problem is known as the 1-41 problem. Both classes have equal probability of occurrence and samples from both classes may appear anywhere throughout the ddimensional space. Most samples near the origin of the coordinate system will be from the first class while most samples away from the origin will be from the second class. Since the two classes completely overlap it is impossible to have a classifier with zero error. The minimum possible error is known as the Bayes error and

  14. Steric sea level variability (1993-2010) in an ensemble of ocean reanalyses and objective analyses

    Science.gov (United States)

    Storto, Andrea; Masina, Simona; Balmaseda, Magdalena; Guinehut, Stéphanie; Xue, Yan; Szekely, Tanguy; Fukumori, Ichiro; Forget, Gael; Chang, You-Soon; Good, Simon A.; Köhl, Armin; Vernieres, Guillaume; Ferry, Nicolas; Peterson, K. Andrew; Behringer, David; Ishii, Masayoshi; Masuda, Shuhei; Fujii, Yosuke; Toyoda, Takahiro; Yin, Yonghong; Valdivieso, Maria; Barnier, Bernard; Boyer, Tim; Lee, Tony; Gourrion, Jérome; Wang, Ou; Heimback, Patrick; Rosati, Anthony; Kovach, Robin; Hernandez, Fabrice; Martin, Matthew J.; Kamachi, Masafumi; Kuragano, Tsurane; Mogensen, Kristian; Alves, Oscar; Haines, Keith; Wang, Xiaochun

    2017-08-01

    Quantifying the effect of the seawater density changes on sea level variability is of crucial importance for climate change studies, as the sea level cumulative rise can be regarded as both an important climate change indicator and a possible danger for human activities in coastal areas. In this work, as part of the Ocean Reanalysis Intercomparison Project, the global and regional steric sea level changes are estimated and compared from an ensemble of 16 ocean reanalyses and 4 objective analyses. These estimates are initially compared with a satellite-derived (altimetry minus gravimetry) dataset for a short period (2003-2010). The ensemble mean exhibits a significant high correlation at both global and regional scale, and the ensemble of ocean reanalyses outperforms that of objective analyses, in particular in the Southern Ocean. The reanalysis ensemble mean thus represents a valuable tool for further analyses, although large uncertainties remain for the inter-annual trends. Within the extended intercomparison period that spans the altimetry era (1993-2010), we find that the ensemble of reanalyses and objective analyses are in good agreement, and both detect a trend of the global steric sea level of 1.0 and 1.1 ± 0.05 mm/year, respectively. However, the spread among the products of the halosteric component trend exceeds the mean trend itself, questioning the reliability of its estimate. This is related to the scarcity of salinity observations before the Argo era. Furthermore, the impact of deep ocean layers is non-negligible on the steric sea level variability (22 and 12 % for the layers below 700 and 1500 m of depth, respectively), although the small deep ocean trends are not significant with respect to the products spread.

  15. A simple and robust statistical framework for planning, analysing and interpreting faecal egg count reduction test (FECRT) studies

    DEFF Research Database (Denmark)

    Denwood, M.J.; McKendrick, I.J.; Matthews, L.

    Introduction. There is an urgent need for a method of analysing FECRT data that is computationally simple and statistically robust. A method for evaluating the statistical power of a proposed FECRT study would also greatly enhance the current guidelines. Methods. A novel statistical framework has...... been developed that evaluates observed FECRT data against two null hypotheses: (1) the observed efficacy is consistent with the expected efficacy, and (2) the observed efficacy is inferior to the expected efficacy. The method requires only four simple summary statistics of the observed data. Power...... that the notional type 1 error rate of the new statistical test is accurate. Power calculations demonstrate a power of only 65% with a sample size of 20 treatment and control animals, which increases to 69% with 40 control animals or 79% with 40 treatment animals. Discussion. The method proposed is simple...

  16. The Relationship Between Radiative Forcing and Temperature. What Do Statistical Analyses of the Instrumental Temperature Record Measure?

    International Nuclear Information System (INIS)

    Kaufmann, R.K.; Kauppi, H.; Stock, J.H.

    2006-01-01

    Comparing statistical estimates for the long-run temperature effect of doubled CO2 with those generated by climate models begs the question, is the long-run temperature effect of doubled CO2 that is estimated from the instrumental temperature record using statistical techniques consistent with the transient climate response, the equilibrium climate sensitivity, or the effective climate sensitivity. Here, we attempt to answer the question, what do statistical analyses of the observational record measure, by using these same statistical techniques to estimate the temperature effect of a doubling in the atmospheric concentration of carbon dioxide from seventeen simulations run for the Coupled Model Intercomparison Project 2 (CMIP2). The results indicate that the temperature effect estimated by the statistical methodology is consistent with the transient climate response and that this consistency is relatively unaffected by sample size or the increase in radiative forcing in the sample

  17. Low-frequency variability of the atmospheric circulation: a comparison of statistical properties in both hemispheres and extreme seasons

    International Nuclear Information System (INIS)

    Buzzi, A.; Tosi, E.

    1988-01-01

    A statistical investigation is presented of the main variables characterizing the tropospheric general circulation in both hemispheres and extreme season, Winter and Summer. This gives up the opportunity of comparing four distinct realizations of the planetary circulation, as function of different orographic and thermal forcing conditions. Our approach is made possible by the availability of 6 years of global daily analyses prepared by ECMWF (European Centre for Medium-range Weather Forecast). The variables taken into account are the zonal geostrophic wind, the zonal thermal wind and various large-scala wave components, averaged over the tropospheric depth between 1000 and 200 hPa. The mean properties of the analysed quantities in each hemisphere and season are compared and their principal characteristics are discussed. The probability density estimates for the same variables, filtered in order to eliminate the seasonal cycle and the high frequency 'noise', are then presented. The distributions are examined, in particular, with respect of their unimodal or multimodal nature and with reference to the recent discussion in the literature on the bimodality which has been found for some indicators of planetary wave activity in the Nothern Hemisphere Winter. Our results indicate the presence of nonunimodally distributed wave and zonal flow components in both hemispheres and extreme season. The most frequent occurrence of nonunimodal behaviour is found for those wave components which exhibit an almost vanishing zonal phase speed and a larger 'response' to orographic forcing

  18. SOERP, Statistics and 2. Order Error Propagation for Function of Random Variables

    International Nuclear Information System (INIS)

    Cox, N. D.; Miller, C. F.

    1985-01-01

    1 - Description of problem or function: SOERP computes second-order error propagation equations for the first four moments of a function of independently distributed random variables. SOERP was written for a rigorous second-order error propagation of any function which may be expanded in a multivariable Taylor series, the input variables being independently distributed. The required input consists of numbers directly related to the partial derivatives of the function, evaluated at the nominal values of the input variables and the central moments of the input variables from the second through the eighth. 2 - Method of solution: The development of equations for computing the propagation of errors begins by expressing the function of random variables in a multivariable Taylor series expansion. The Taylor series expansion is then truncated, and statistical operations are applied to the series in order to obtain equations for the moments (about the origin) of the distribution of the computed value. If the Taylor series is truncated after powers of two, the procedure produces second-order error propagation equations. 3 - Restrictions on the complexity of the problem: The maximum number of component variables allowed is 30. The IBM version will only process one set of input data per run

  19. Statistical analyses of the magnet data for the advanced photon source storage ring magnets

    International Nuclear Information System (INIS)

    Kim, S.H.; Carnegie, D.W.; Doose, C.; Hogrefe, R.; Kim, K.; Merl, R.

    1995-01-01

    The statistics of the measured magnetic data of 80 dipole, 400 quadrupole, and 280 sextupole magnets of conventional resistive designs for the APS storage ring is summarized. In order to accommodate the vacuum chamber, the curved dipole has a C-type cross section and the quadrupole and sextupole cross sections have 180 degrees and 120 degrees symmetries, respectively. The data statistics include the integrated main fields, multipole coefficients, magnetic and mechanical axes, and roll angles of the main fields. The average and rms values of the measured magnet data meet the storage ring requirements

  20. "Who Was 'Shadow'?" The Computer Knows: Applying Grammar-Program Statistics in Content Analyses to Solve Mysteries about Authorship.

    Science.gov (United States)

    Ellis, Barbara G.; Dick, Steven J.

    1996-01-01

    Employs the statistics-documentation portion of a word-processing program's grammar-check feature together with qualitative analyses to determine that Henry Watterson, long-time editor of the "Louisville Courier-Journal," was probably the South's famed Civil War correspondent "Shadow." (TB)

  1. Design and implementation of a modular program system for the carrying-through of statistical analyses

    International Nuclear Information System (INIS)

    Beck, W.

    1984-01-01

    From the complexity of computer programs for the solution of scientific and technical problems results a lot of questions. Typical questions concern the strength and weakness of computer programs, the propagation of incertainties among the input data, the sensitivity of input data on output data and the substitute of complex models by more simple ones, which provide equivalent results in certain ranges. Those questions have a general practical meaning, principle answers may be found by statistical methods, which are based on the Monte Carlo Method. In this report the statistical methods are chosen, described and valuated. They are implemented into the modular program system STAR, which is an own component of the program system RSYST. The design of STAR considers users with different knowledge of data processing and statistics. The variety of statistical methods, generating and evaluating procedures. The processing of large data sets in complex structures. The coupling to other components of RSYST and RSYST foreign programs. That the system can be easily modificated and enlarged. Four examples are given, which demonstrate the application of STAR. (orig.) [de

  2. Age and gender effects on normal regional cerebral blood flow studied using two different voxel-based statistical analyses

    International Nuclear Information System (INIS)

    Pirson, A.S.; George, J.; Krug, B.; Vander Borght, T.; Van Laere, K.; Jamart, J.; D'Asseler, Y.; Minoshima, S.

    2009-01-01

    Fully automated analysis programs have been applied more and more to aid for the reading of regional cerebral blood flow SPECT study. They are increasingly based on the comparison of the patient study with a normal database. In this study, we evaluate the ability of Three-Dimensional Stereotactic Surface Projection (3 D-S.S.P.) to isolate effects of age and gender in a previously studied normal population. The results were also compared with those obtained using Statistical Parametric Mapping (S.P.M.99). Methods Eighty-nine 99m Tc-E.C.D.-SPECT studies performed in carefully screened healthy volunteers (46 females, 43 males; age 20 - 81 years) were analysed using 3 D-S.S.P.. A multivariate analysis based on the general linear model was performed with regions as intra-subject factor, gender as inter-subject factor and age as co-variate. Results Both age and gender had a significant interaction effect with regional tracer uptake. An age-related decline (p < 0.001) was found in the anterior cingulate gyrus, left frontal association cortex and left insula. Bilateral occipital association and left primary visual cortical uptake showed a significant relative increase with age (p < 0.001). Concerning the gender effect, women showed higher uptake (p < 0.01) in the parietal and right sensorimotor cortices. An age by gender interaction (p < 0.01) was only found in the left medial frontal cortex. The results were consistent with those obtained with S.P.M.99. Conclusion 3 D-S.S.P. analysis of normal r.C.B.F. variability is consistent with the literature and other automated voxel-based techniques, which highlight the effects of both age and gender. (authors)

  3. Exact statistical results for binary mixing and reaction in variable density turbulence

    Science.gov (United States)

    Ristorcelli, J. R.

    2017-02-01

    We report a number of rigorous statistical results on binary active scalar mixing in variable density turbulence. The study is motivated by mixing between pure fluids with very different densities and whose density intensity is of order unity. Our primary focus is the derivation of exact mathematical results for mixing in variable density turbulence and we do point out the potential fields of application of the results. A binary one step reaction is invoked to derive a metric to asses the state of mixing. The mean reaction rate in variable density turbulent mixing can be expressed, in closed form, using the first order Favre mean variables and the Reynolds averaged density variance, ⟨ρ2⟩ . We show that the normalized density variance, ⟨ρ2⟩ , reflects the reduction of the reaction due to mixing and is a mix metric. The result is mathematically rigorous. The result is the variable density analog, the normalized mass fraction variance ⟨c2⟩ used in constant density turbulent mixing. As a consequence, we demonstrate that use of the analogous normalized Favre variance of the mass fraction, c″ ⁣2˜ , as a mix metric is not theoretically justified in variable density turbulence. We additionally derive expressions relating various second order moments of the mass fraction, specific volume, and density fields. The central role of the density specific volume covariance ⟨ρ v ⟩ is highlighted; it is a key quantity with considerable dynamical significance linking various second order statistics. For laboratory experiments, we have developed exact relations between the Reynolds scalar variance ⟨c2⟩ its Favre analog c″ ⁣2˜ , and various second moments including ⟨ρ v ⟩ . For moment closure models that evolve ⟨ρ v ⟩ and not ⟨ρ2⟩ , we provide a novel expression for ⟨ρ2⟩ in terms of a rational function of ⟨ρ v ⟩ that avoids recourse to Taylor series methods (which do not converge for large density differences). We have derived

  4. Statistical Modelling of Synaptic Vesicles Distribution and Analysing their Physical Characteristics

    DEFF Research Database (Denmark)

    Khanmohammadi, Mahdieh

    transmission electron microscopy is used to acquire images from two experimental groups of rats: 1) rats subjected to a behavioral model of stress and 2) rats subjected to sham stress as the control group. The synaptic vesicle distribution and interactions are modeled by employing a point process approach......This Ph.D. thesis deals with mathematical and statistical modeling of synaptic vesicle distribution, shape, orientation and interactions. The first major part of this thesis treats the problem of determining the effect of stress on synaptic vesicle distribution and interactions. Serial section...... on differences of statistical measures in section and the same measures in between sections. Three-dimensional (3D) datasets are reconstructed by using image registration techniques and estimated thicknesses. We distinguish the effect of stress by estimating the synaptic vesicle densities and modeling...

  5. Statistic analyses of the color experience according to the age of the observer.

    Science.gov (United States)

    Hunjet, Anica; Parac-Osterman, Durdica; Vucaj, Edita

    2013-04-01

    Psychological experience of color is a real state of the communication between the environment and color, and it will depend on the source of the light, angle of the view, and particular on the observer and his health condition. Hering's theory or a theory of the opponent processes supposes that cones, which are situated in the retina of the eye, are not sensible on the three chromatic domains (areas, fields, zones) (red, green and purple-blue), but they produce a signal based on the principle of the opposed pairs of colors. A reason of this theory depends on the fact that certain disorders of the color eyesight, which include blindness to certain colors, cause blindness to pairs of opponent colors. This paper presents a demonstration of the experience of blue and yellow tone according to the age of the observer. For the testing of the statistically significant differences in the omission in the color experience according to the color of the background we use following statistical tests: Mann-Whitnney U Test, Kruskal-Wallis ANOVA and Median test. It was proven that the differences are statistically significant in the elderly persons (older than 35 years).

  6. Statistical analyses of the performance of Macedonian investment and pension funds

    Directory of Open Access Journals (Sweden)

    Petar Taleski

    2015-10-01

    Full Text Available The foundation of the post-modern portfolio theory is creating a portfolio based on a desired target return. This specifically applies to the performance of investment and pension funds that provide a rate of return meeting payment requirements from investment funds. A desired target return is the goal of an investment or pension fund. It is the primary benchmark used to measure performances, dynamic monitoring and evaluation of the risk–return ratio on investment funds. The analysis in this paper is based on monthly returns of Macedonian investment and pension funds (June 2011 - June 2014. Such analysis utilizes the basic, but highly informative statistical characteristic moments like skewness, kurtosis, Jarque–Bera, and Chebyishev’s Inequality. The objective of this study is to perform a trough analysis, utilizing the above mentioned and other types of statistical techniques (Sharpe, Sortino, omega, upside potential, Calmar, Sterling to draw relevant conclusions regarding the risks and characteristic moments in Macedonian investment and pension funds. Pension funds are the second largest segment of the financial system, and has great potential for further growth due to constant inflows from pension insurance. The importance of investment funds for the financial system in the Republic of Macedonia is still small, although open-end investment funds have been the fastest growing segment of the financial system. Statistical analysis has shown that pension funds have delivered a significantly positive volatility-adjusted risk premium in the analyzed period more so than investment funds.

  7. Robust statistics for deterministic and stochastic gravitational waves in non-Gaussian noise. II. Bayesian analyses

    International Nuclear Information System (INIS)

    Allen, Bruce; Creighton, Jolien D.E.; Flanagan, Eanna E.; Romano, Joseph D.

    2003-01-01

    In a previous paper (paper I), we derived a set of near-optimal signal detection techniques for gravitational wave detectors whose noise probability distributions contain non-Gaussian tails. The methods modify standard methods by truncating or clipping sample values which lie in those non-Gaussian tails. The methods were derived, in the frequentist framework, by minimizing false alarm probabilities at fixed false detection probability in the limit of weak signals. For stochastic signals, the resulting statistic consisted of a sum of an autocorrelation term and a cross-correlation term; it was necessary to discard 'by hand' the autocorrelation term in order to arrive at the correct, generalized cross-correlation statistic. In the present paper, we present an alternative derivation of the same signal detection techniques from within the Bayesian framework. We compute, for both deterministic and stochastic signals, the probability that a signal is present in the data, in the limit where the signal-to-noise ratio squared per frequency bin is small, where the signal is nevertheless strong enough to be detected (integrated signal-to-noise ratio large compared to 1), and where the total probability in the non-Gaussian tail part of the noise distribution is small. We show that, for each model considered, the resulting probability is to a good approximation a monotonic function of the detection statistic derived in paper I. Moreover, for stochastic signals, the new Bayesian derivation automatically eliminates the problematic autocorrelation term

  8. Why weight? Modelling sample and observational level variability improves power in RNA-seq analyses.

    Science.gov (United States)

    Liu, Ruijie; Holik, Aliaksei Z; Su, Shian; Jansz, Natasha; Chen, Kelan; Leong, Huei San; Blewitt, Marnie E; Asselin-Labat, Marie-Liesse; Smyth, Gordon K; Ritchie, Matthew E

    2015-09-03

    Variations in sample quality are frequently encountered in small RNA-sequencing experiments, and pose a major challenge in a differential expression analysis. Removal of high variation samples reduces noise, but at a cost of reducing power, thus limiting our ability to detect biologically meaningful changes. Similarly, retaining these samples in the analysis may not reveal any statistically significant changes due to the higher noise level. A compromise is to use all available data, but to down-weight the observations from more variable samples. We describe a statistical approach that facilitates this by modelling heterogeneity at both the sample and observational levels as part of the differential expression analysis. At the sample level this is achieved by fitting a log-linear variance model that includes common sample-specific or group-specific parameters that are shared between genes. The estimated sample variance factors are then converted to weights and combined with observational level weights obtained from the mean-variance relationship of the log-counts-per-million using 'voom'. A comprehensive analysis involving both simulations and experimental RNA-sequencing data demonstrates that this strategy leads to a universally more powerful analysis and fewer false discoveries when compared to conventional approaches. This methodology has wide application and is implemented in the open-source 'limma' package. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

  9. Statistics

    CERN Document Server

    Hayslett, H T

    1991-01-01

    Statistics covers the basic principles of Statistics. The book starts by tackling the importance and the two kinds of statistics; the presentation of sample data; the definition, illustration and explanation of several measures of location; and the measures of variation. The text then discusses elementary probability, the normal distribution and the normal approximation to the binomial. Testing of statistical hypotheses and tests of hypotheses about the theoretical proportion of successes in a binomial population and about the theoretical mean of a normal population are explained. The text the

  10. The number of subjects per variable required in linear regression analyses.

    Science.gov (United States)

    Austin, Peter C; Steyerberg, Ewout W

    2015-06-01

    To determine the number of independent variables that can be included in a linear regression model. We used a series of Monte Carlo simulations to examine the impact of the number of subjects per variable (SPV) on the accuracy of estimated regression coefficients and standard errors, on the empirical coverage of estimated confidence intervals, and on the accuracy of the estimated R(2) of the fitted model. A minimum of approximately two SPV tended to result in estimation of regression coefficients with relative bias of less than 10%. Furthermore, with this minimum number of SPV, the standard errors of the regression coefficients were accurately estimated and estimated confidence intervals had approximately the advertised coverage rates. A much higher number of SPV were necessary to minimize bias in estimating the model R(2), although adjusted R(2) estimates behaved well. The bias in estimating the model R(2) statistic was inversely proportional to the magnitude of the proportion of variation explained by the population regression model. Linear regression models require only two SPV for adequate estimation of regression coefficients, standard errors, and confidence intervals. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

  11. Towards an Industrial Application of Statistical Uncertainty Analysis Methods to Multi-physical Modelling and Safety Analyses

    International Nuclear Information System (INIS)

    Zhang, Jinzhao; Segurado, Jacobo; Schneidesch, Christophe

    2013-01-01

    Since 1980's, Tractebel Engineering (TE) has being developed and applied a multi-physical modelling and safety analyses capability, based on a code package consisting of the best estimate 3D neutronic (PANTHER), system thermal hydraulic (RELAP5), core sub-channel thermal hydraulic (COBRA-3C), and fuel thermal mechanic (FRAPCON/FRAPTRAN) codes. A series of methodologies have been developed to perform and to license the reactor safety analysis and core reload design, based on the deterministic bounding approach. Following the recent trends in research and development as well as in industrial applications, TE has been working since 2010 towards the application of the statistical sensitivity and uncertainty analysis methods to the multi-physical modelling and licensing safety analyses. In this paper, the TE multi-physical modelling and safety analyses capability is first described, followed by the proposed TE best estimate plus statistical uncertainty analysis method (BESUAM). The chosen statistical sensitivity and uncertainty analysis methods (non-parametric order statistic method or bootstrap) and tool (DAKOTA) are then presented, followed by some preliminary results of their applications to FRAPCON/FRAPTRAN simulation of OECD RIA fuel rod codes benchmark and RELAP5/MOD3.3 simulation of THTF tests. (authors)

  12. An Empirical Study of Presage Variables in the Teaching-Learning of Statistics, in the Light of Research on Competencies

    Science.gov (United States)

    Rodriguez, Clemente; Gutierrez-Perez, Jose; Pozo, Teresa

    2010-01-01

    Introduction: This research seeks to determine the influence exercised by a set of presage and process variables (students' pre-existing opinion towards statistics, their dedication to mastery of statistics content, assessment of the teaching materials, and the teacher's effort in the teaching of statistics) in students' resolution of activities…

  13. Developing Students' Reasoning about Samples and Sampling Variability as a Path to Expert Statistical Thinking

    Science.gov (United States)

    Garfield, Joan; Le, Laura; Zieffler, Andrew; Ben-Zvi, Dani

    2015-01-01

    This paper describes the importance of developing students' reasoning about samples and sampling variability as a foundation for statistical thinking. Research on expert-novice thinking as well as statistical thinking is reviewed and compared. A case is made that statistical thinking is a type of expert thinking, and as such, research…

  14. Meta-Statistics for Variable Selection: The R Package BioMark

    Directory of Open Access Journals (Sweden)

    Ron Wehrens

    2012-11-01

    Full Text Available Biomarker identification is an ever more important topic in the life sciences. With the advent of measurement methodologies based on microarrays and mass spectrometry, thousands of variables are routinely being measured on complex biological samples. Often, the question is what makes two groups of samples different. Classical hypothesis testing suffers from the multiple testing problem; however, correcting for this often leads to a lack of power. In addition, choosing α cutoff levels remains somewhat arbitrary. Also in a regression context, a model depending on few but relevant variables will be more accurate and precise, and easier to interpret biologically.We propose an R package, BioMark, implementing two meta-statistics for variable selection. The first, higher criticism, presents a data-dependent selection threshold for significance, instead of a cookbook value of α = 0.05. It is applicable in all cases where two groups are compared. The second, stability selection, is more general, and can also be applied in a regression context. This approach uses repeated subsampling of the data in order to assess the variability of the model coefficients and selects those that remain consistently important. It is shown using experimental spike-in data from the field of metabolomics that both approaches work well with real data. BioMark also contains functionality for simulating data with specific characteristics for algorithm development and testing.

  15. Dispersal of potato cyst nematodes measured using historical and spatial statistical analyses.

    Science.gov (United States)

    Banks, N C; Hodda, M; Singh, S K; Matveeva, E M

    2012-06-01

    Rates and modes of dispersal of potato cyst nematodes (PCNs) were investigated. Analysis of records from eight countries suggested that PCNs spread a mean distance of 5.3 km/year radially from the site of first detection, and spread 212 km over ≈40 years before detection. Data from four countries with more detailed histories of invasion were analyzed further, using distance from first detection, distance from previous detection, distance from nearest detection, straight line distance, and road distance. Linear distance from first detection was significantly related to the time since the first detection. Estimated rate of spread was 5.7 km/year, and did not differ statistically between countries. Time between the first detection and estimated introduction date varied between 0 and 20 years, and differed among countries. Road distances from nearest and first detection were statistically significantly related to time, and gave slightly higher estimates for rate of spread of 6.0 and 7.9 km/year, respectively. These results indicate that the original site of introduction of PCNs may act as a source for subsequent spread and that this may occur at a relatively constant rate over time regardless of whether this distance is measured by road or by a straight line. The implications of this constant radial rate of dispersal for biosecurity and pest management are discussed, along with the effects of control strategies.

  16. Complex analyses of inverted repeats in mitochondrial genomes revealed their importance and variability.

    Science.gov (United States)

    Cechová, Jana; Lýsek, Jirí; Bartas, Martin; Brázda, Václav

    2018-04-01

    The NCBI database contains mitochondrial DNA (mtDNA) genomes from numerous species. We investigated the presence and locations of inverted repeat sequences (IRs) in these mtDNA sequences, which are known to be important for regulating nuclear genomes. IRs were identified in mtDNA in all species. IR lengths and frequencies correlate with evolutionary age and the greatest variability was detected in subgroups of plants and fungi and the lowest variability in mammals. IR presence is non-random and evolutionary favoured. The frequency of IRs generally decreased with IR length, but not for IRs 24 or 30 bp long, which are 1.5 times more abundant. IRs are enriched in sequences from the replication origin, followed by D-loop, stem-loop and miscellaneous sequences, pointing to the importance of IRs in regulatory regions of mitochondrial DNA. Data were produced using Palindrome analyser, freely available on the web at http://bioinformatics.ibp.cz. vaclav@ibp.cz. Supplementary data are available at Bioinformatics online.

  17. Analysing inter-relationships among water, governance, human development variables in developing countries

    Science.gov (United States)

    Dondeynaz, C.; Carmona Moreno, C.; Céspedes Lorente, J. J.

    2012-10-01

    The "Integrated Water Resources Management" principle was formally laid down at the International Conference on Water and Sustainable development in Dublin 1992. One of the main results of this conference is that improving Water and Sanitation Services (WSS), being a complex and interdisciplinary issue, passes through collaboration and coordination of different sectors (environment, health, economic activities, governance, and international cooperation). These sectors influence or are influenced by the access to WSS. The understanding of these interrelations appears as crucial for decision makers in the water sector. In this framework, the Joint Research Centre (JRC) of the European Commission (EC) has developed a new database (WatSan4Dev database) containing 42 indicators (called variables in this paper) from environmental, socio-economic, governance and financial aid flows data in developing countries. This paper describes the development of the WatSan4Dev dataset, the statistical processes needed to improve the data quality, and finally, the analysis to verify the database coherence is presented. Based on 25 relevant variables, the relationships between variables are described and organised into five factors (HDP - Human Development against Poverty, AP - Human Activity Pressure on water resources, WR - Water Resources, ODA - Official Development Aid, CEC - Country Environmental Concern). Linear regression methods are used to identify key variables having influence on water supply and sanitation. First analysis indicates that the informal urbanisation development is an important factor negatively influencing the percentage of the population having access to WSS. Health, and in particular children's health, benefits from the improvement of WSS. Irrigation is also enhancing Water Supply service thanks to multi-purpose infrastructure. Five country profiles are also created to deeper understand and synthetize the amount of information gathered. This new

  18. Analysing inter-relationships among water, governance, human development variables in developing countries

    Directory of Open Access Journals (Sweden)

    C. Dondeynaz

    2012-10-01

    Full Text Available The "Integrated Water Resources Management" principle was formally laid down at the International Conference on Water and Sustainable development in Dublin 1992. One of the main results of this conference is that improving Water and Sanitation Services (WSS, being a complex and interdisciplinary issue, passes through collaboration and coordination of different sectors (environment, health, economic activities, governance, and international cooperation. These sectors influence or are influenced by the access to WSS. The understanding of these interrelations appears as crucial for decision makers in the water sector. In this framework, the Joint Research Centre (JRC of the European Commission (EC has developed a new database (WatSan4Dev database containing 42 indicators (called variables in this paper from environmental, socio-economic, governance and financial aid flows data in developing countries. This paper describes the development of the WatSan4Dev dataset, the statistical processes needed to improve the data quality, and finally, the analysis to verify the database coherence is presented. Based on 25 relevant variables, the relationships between variables are described and organised into five factors (HDP – Human Development against Poverty, AP – Human Activity Pressure on water resources, WR – Water Resources, ODA – Official Development Aid, CEC – Country Environmental Concern. Linear regression methods are used to identify key variables having influence on water supply and sanitation. First analysis indicates that the informal urbanisation development is an important factor negatively influencing the percentage of the population having access to WSS. Health, and in particular children's health, benefits from the improvement of WSS. Irrigation is also enhancing Water Supply service thanks to multi-purpose infrastructure. Five country profiles are also created to deeper understand and synthetize the amount of information gathered

  19. Statistical Analyses and Modeling of the Implementation of Agile Manufacturing Tactics in Industrial Firms

    Directory of Open Access Journals (Sweden)

    Mohammad D. AL-Tahat

    2012-01-01

    Full Text Available This paper provides a review and introduction on agile manufacturing. Tactics of agile manufacturing are mapped into different production areas (eight-construct latent: manufacturing equipment and technology, processes technology and know-how, quality and productivity improvement, production planning and control, shop floor management, product design and development, supplier relationship management, and customer relationship management. The implementation level of agile manufacturing tactics is investigated in each area. A structural equation model is proposed. Hypotheses are formulated. Feedback from 456 firms is collected using five-point-Likert-scale questionnaire. Statistical analysis is carried out using IBM SPSS and AMOS. Multicollinearity, content validity, consistency, construct validity, ANOVA analysis, and relationships between agile components are tested. The results of this study prove that the agile manufacturing tactics have positive effect on the overall agility level. This conclusion can be used by manufacturing firms to manage challenges when trying to be agile.

  20. Municipal solid waste composition: Sampling methodology, statistical analyses, and case study evaluation

    DEFF Research Database (Denmark)

    Edjabou, Vincent Maklawe Essonanawe; Jensen, Morten Bang; Götze, Ramona

    2015-01-01

    Sound waste management and optimisation of resource recovery require reliable data on solid waste generation and composition. In the absence of standardised and commonly accepted waste characterisation methodologies, various approaches have been reported in literature. This limits both...... comparability and applicability of the results. In this study, a waste sampling and sorting methodology for efficient and statistically robust characterisation of solid waste was introduced. The methodology was applied to residual waste collected from 1442 households distributed among 10 individual sub......-areas in three Danish municipalities (both single and multi-family house areas). In total 17 tonnes of waste were sorted into 10-50 waste fractions, organised according to a three-level (tiered approach) facilitating,comparison of the waste data between individual sub-areas with different fractionation (waste...

  1. Statistics

    Science.gov (United States)

    Links to sources of cancer-related statistics, including the Surveillance, Epidemiology and End Results (SEER) Program, SEER-Medicare datasets, cancer survivor prevalence data, and the Cancer Trends Progress Report.

  2. On statistical methods for analysing the geographical distribution of cancer cases near nuclear installations

    International Nuclear Information System (INIS)

    Bithell, J.F.; Stone, R.A.

    1989-01-01

    This paper sets out to show that epidemiological methods most commonly used can be improved. When analysing geographical data it is necessary to consider location. The most obvious quantification of location is ranked distance, though other measures which may be more meaningful in relation to aetiology may be substituted. A test based on distance ranks, the ''Poisson maximum test'', depends on the maximum of observed relative risk in regions of increasing size, but with significance level adjusted for selection. Applying this test to data from Sellafield and Sizewell shows that the excess of leukaemia incidence observed at Seascale, near Sellafield, is not an artefact due to data selection by region, and that the excess probably results from a genuine, if as yet unidentified cause (there being little evidence of any other locational association once the Seascale cases have been removed). So far as Sizewell is concerned, geographical proximity to the nuclear power station does not seen particularly important. (author)

  3. Statistical Learning and Adaptive Decision-Making Underlie Human Response Time Variability in Inhibitory Control

    Directory of Open Access Journals (Sweden)

    Ning eMa

    2015-08-01

    Full Text Available Response time (RT is an oft-reported behavioral measure in psychological and neurocognitive experiments, but the high level of observed trial-to-trial variability in this measure has often limited its usefulness. Here, we combine computational modeling and psychophysics to examine the hypothesis that fluctuations in this noisy measure reflect dynamic computations in human statistical learning and corresponding cognitive adjustments. We present data from the stop-signal task, in which subjects respond to a go stimulus on each trial, unless instructed not to by a subsequent, infrequently presented stop signal. We model across-trial learning of stop signal frequency, P(stop, and stop-signal onset time, SSD (stop-signal delay, with a Bayesian hidden Markov model, and within-trial decision-making with an optimal stochastic control model. The combined model predicts that RT should increase with both expected P(stop and SSD. The human behavioral data (n=20 bear out this prediction, showing P(stop and SSD both to be significant, independent predictors of RT, with P(stop being a more prominent predictor in 75% of the subjects, and SSD being more prominent in the remaining 25%. The results demonstrate that humans indeed readily internalize environmental statistics and adjust their cognitive/behavioral strategy accordingly, and that subtle patterns in RT variability can serve as a valuable tool for validating models of statistical learning and decision-making. More broadly, the modeling tools presented in this work can be generalized to a large body of behavioral paradigms, in order to extract insights about cognitive and neural processing from apparently quite noisy behavioral measures. We also discuss how this behaviorally validated model can then be used to conduct model-based analysis of neural data, in order to help identify specific brain areas for representing and encoding key computational quantities in learning and decision-making.

  4. Statistical learning and adaptive decision-making underlie human response time variability in inhibitory control.

    Science.gov (United States)

    Ma, Ning; Yu, Angela J

    2015-01-01

    Response time (RT) is an oft-reported behavioral measure in psychological and neurocognitive experiments, but the high level of observed trial-to-trial variability in this measure has often limited its usefulness. Here, we combine computational modeling and psychophysics to examine the hypothesis that fluctuations in this noisy measure reflect dynamic computations in human statistical learning and corresponding cognitive adjustments. We present data from the stop-signal task (SST), in which subjects respond to a go stimulus on each trial, unless instructed not to by a subsequent, infrequently presented stop signal. We model across-trial learning of stop signal frequency, P(stop), and stop-signal onset time, SSD (stop-signal delay), with a Bayesian hidden Markov model, and within-trial decision-making with an optimal stochastic control model. The combined model predicts that RT should increase with both expected P(stop) and SSD. The human behavioral data (n = 20) bear out this prediction, showing P(stop) and SSD both to be significant, independent predictors of RT, with P(stop) being a more prominent predictor in 75% of the subjects, and SSD being more prominent in the remaining 25%. The results demonstrate that humans indeed readily internalize environmental statistics and adjust their cognitive/behavioral strategy accordingly, and that subtle patterns in RT variability can serve as a valuable tool for validating models of statistical learning and decision-making. More broadly, the modeling tools presented in this work can be generalized to a large body of behavioral paradigms, in order to extract insights about cognitive and neural processing from apparently quite noisy behavioral measures. We also discuss how this behaviorally validated model can then be used to conduct model-based analysis of neural data, in order to help identify specific brain areas for representing and encoding key computational quantities in learning and decision-making.

  5. Autonomic Differentiation Map: A Novel Statistical Tool for Interpretation of Heart Rate Variability

    Directory of Open Access Journals (Sweden)

    Daniela Lucini

    2018-04-01

    Full Text Available In spite of the large body of evidence suggesting Heart Rate Variability (HRV alone or combined with blood pressure variability (providing an estimate of baroreflex gain as a useful technique to assess the autonomic regulation of the cardiovascular system, there is still an ongoing debate about methodology, interpretation, and clinical applications. In the present investigation, we hypothesize that non-parametric and multivariate exploratory statistical manipulation of HRV data could provide a novel informational tool useful to differentiate normal controls from clinical groups, such as athletes, or subjects affected by obesity, hypertension, or stress. With a data-driven protocol in 1,352 ambulant subjects, we compute HRV and baroreflex indices from short-term data series as proxies of autonomic (ANS regulation. We apply a three-step statistical procedure, by first removing age and gender effects. Subsequently, by factor analysis, we extract four ANS latent domains that detain the large majority of information (86.94%, subdivided in oscillatory (40.84%, amplitude (18.04%, pressure (16.48%, and pulse domains (11.58%. Finally, we test the overall capacity to differentiate clinical groups vs. control. To give more practical value and improve readability, statistical results concerning individual discriminant ANS proxies and ANS differentiation profiles are displayed through peculiar graphical tools, i.e., significance diagram and ANS differentiation map, respectively. This approach, which simultaneously uses all available information about the system, shows what domains make up the difference in ANS discrimination. e.g., athletes differ from controls in all domains, but with a graded strength: maximal in the (normalized oscillatory and in the pulse domains, slightly less in the pressure domain and minimal in the amplitude domain. The application of multiple (non-parametric and exploratory statistical and graphical tools to ANS proxies defines

  6. Statistical improvements in functional magnetic resonance imaging analyses produced by censoring high-motion data points.

    Science.gov (United States)

    Siegel, Joshua S; Power, Jonathan D; Dubis, Joseph W; Vogel, Alecia C; Church, Jessica A; Schlaggar, Bradley L; Petersen, Steven E

    2014-05-01

    Subject motion degrades the quality of task functional magnetic resonance imaging (fMRI) data. Here, we test two classes of methods to counteract the effects of motion in task fMRI data: (1) a variety of motion regressions and (2) motion censoring ("motion scrubbing"). In motion regression, various regressors based on realignment estimates were included as nuisance regressors in general linear model (GLM) estimation. In motion censoring, volumes in which head motion exceeded a threshold were withheld from GLM estimation. The effects of each method were explored in several task fMRI data sets and compared using indicators of data quality and signal-to-noise ratio. Motion censoring decreased variance in parameter estimates within- and across-subjects, reduced residual error in GLM estimation, and increased the magnitude of statistical effects. Motion censoring performed better than all forms of motion regression and also performed well across a variety of parameter spaces, in GLMs with assumed or unassumed response shapes. We conclude that motion censoring improves the quality of task fMRI data and can be a valuable processing step in studies involving populations with even mild amounts of head movement. Copyright © 2013 Wiley Periodicals, Inc.

  7. Accounting for undetected compounds in statistical analyses of mass spectrometry 'omic studies.

    Science.gov (United States)

    Taylor, Sandra L; Leiserowitz, Gary S; Kim, Kyoungmi

    2013-12-01

    Mass spectrometry is an important high-throughput technique for profiling small molecular compounds in biological samples and is widely used to identify potential diagnostic and prognostic compounds associated with disease. Commonly, this data generated by mass spectrometry has many missing values resulting when a compound is absent from a sample or is present but at a concentration below the detection limit. Several strategies are available for statistically analyzing data with missing values. The accelerated failure time (AFT) model assumes all missing values result from censoring below a detection limit. Under a mixture model, missing values can result from a combination of censoring and the absence of a compound. We compare power and estimation of a mixture model to an AFT model. Based on simulated data, we found the AFT model to have greater power to detect differences in means and point mass proportions between groups. However, the AFT model yielded biased estimates with the bias increasing as the proportion of observations in the point mass increased while estimates were unbiased with the mixture model except if all missing observations came from censoring. These findings suggest using the AFT model for hypothesis testing and mixture model for estimation. We demonstrated this approach through application to glycomics data of serum samples from women with ovarian cancer and matched controls.

  8. Introduction to statistical modelling 2: categorical variables and interactions in linear regression.

    Science.gov (United States)

    Lunt, Mark

    2015-07-01

    In the first article in this series we explored the use of linear regression to predict an outcome variable from a number of predictive factors. It assumed that the predictive factors were measured on an interval scale. However, this article shows how categorical variables can also be included in a linear regression model, enabling predictions to be made separately for different groups and allowing for testing the hypothesis that the outcome differs between groups. The use of interaction terms to measure whether the effect of a particular predictor variable differs between groups is also explained. An alternative approach to testing the difference between groups of the effect of a given predictor, which consists of measuring the effect in each group separately and seeing whether the statistical significance differs between the groups, is shown to be misleading. © The Author 2013. Published by Oxford University Press on behalf of the British Society for Rheumatology. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  9. Statistical analysis of nuclear power plant pump failure rate variability: some preliminary results

    International Nuclear Information System (INIS)

    Martz, H.F.; Whiteman, D.E.

    1984-02-01

    In-Plant Reliability Data System (IPRDS) pump failure data on over 60 selected pumps in four nuclear power plants are statistically analyzed using the Failure Rate Analysis Code (FRAC). A major purpose of the analysis is to determine which environmental, system, and operating factors adequately explain the variability in the failure data. Catastrophic, degraded, and incipient failure severity categories are considered for both demand-related and time-dependent failures. For catastrophic demand-related pump failures, the variability is explained by the following factors listed in their order of importance: system application, pump driver, operating mode, reactor type, pump type, and unidentified plant-specific influences. Quantitative failure rate adjustments are provided for the effects of these factors. In the case of catastrophic time-dependent pump failures, the failure rate variability is explained by three factors: reactor type, pump driver, and unidentified plant-specific influences. Finally, point and confidence interval failure rate estimates are provided for each selected pump by considering the influential factors. Both types of estimates represent an improvement over the estimates computed exclusively from the data on each pump

  10. STATISTIC, PROBABILISTIC, CORRELATION AND SPECTRAL ANALYSES OF REGENERATIVE BRAKING CURRENT OF DC ELECTRIC ROLLING STOCK

    Directory of Open Access Journals (Sweden)

    A. V. Nikitenko

    2014-04-01

    Full Text Available Purpose. Defining and analysis of the probabilistic and spectral characteristics of random current in regenerative braking mode of DC electric rolling stock are observed in this paper. Methodology. The elements and methods of the probability theory (particularly the theory of stationary and non-stationary processes and methods of the sampling theory are used for processing of the regenerated current data arrays by PC. Findings. The regenerated current records are obtained from the locomotives and trains in Ukraine railways and trams in Poland. It was established that the current has uninterrupted and the jumping variations in time (especially in trams. For the random current in the regenerative braking mode the functions of mathematical expectation, dispersion and standard deviation are calculated. Histograms, probabilistic characteristics and correlation functions are calculated and plotted down for this current too. It was established that the current of the regenerative braking mode can be considered like the stationary and non-ergodic process. The spectral analysis of these records and “tail part” of the correlation function found weak periodical (or low-frequency components which are known like an interharmonic. Originality. Firstly, the theory of non-stationary random processes was adapted for the analysis of the recuperated current which has uninterrupted and the jumping variations in time. Secondly, the presence of interharmonics in the stochastic process of regenerated current was defined for the first time. And finally, the patterns of temporal changes of the correlation current function are defined too. This allows to reasonably apply the correlation functions method in the identification of the electric traction system devices. Practical value. The results of probabilistic and statistic analysis of the recuperated current allow to estimate the quality of recovered energy and energy quality indices of electric rolling stock in the

  11. Measurements and statistical analyses of indoor radon concentrations in Tokyo and surrounding areas

    International Nuclear Information System (INIS)

    Sugiura, Shiroharu; Suzuki, Takashi; Inokoshi, Yukio

    1995-01-01

    Since the UNSCEAR report published in 1982, radiation exposure to the respiratory tract due to radon and its progeny has been regarded as the single largest contributor to the natural radiation exposure of the general public. In Japan, the measurement of radon gas concentrations in many types of buildings have been surveyed by national and private institutes. We also carried out the measurement of radon gas concentrations in different types of residential buildings in Tokyo and its adjoining prefectures from October 1988 to September 1991, to evaluate the potential radiation risk of the people living there. One or two simplified passive radon monitors were set up in each of the 34 residential buildings located in the above-mentioned area for an exposure period of 3 months each. Comparing the average concentrations in the buildings of different materials and structures, those in the concrete steel buildings were always higher than those in the wooden and the prefabricated mortared buildings. The radon concentrations were proved to become higher in autumn and winter, and lower in spring and summer. Radon concentrations in an underground room of a concrete steel building showed the highest value throughout our investigation, and statistically significant seasonal variation was detected by the X-11 method developed by the U.S. Bureau of Census. The values measured in a room at the first floor of the same concrete steel building also showed seasonal variation, but the phase of variation was different. Another multivariate analysis suggested that the building material and structure are the most important factors concerning the levels of radon concentration among other factors such as the age of the building and the use of ventilators. (author)

  12. Computational and Statistical Analyses of Insertional Polymorphic Endogenous Retroviruses in a Non-Model Organism

    Directory of Open Access Journals (Sweden)

    Le Bao

    2014-11-01

    Full Text Available Endogenous retroviruses (ERVs are a class of transposable elements found in all vertebrate genomes that contribute substantially to genomic functional and structural diversity. A host species acquires an ERV when an exogenous retrovirus infects a germ cell of an individual and becomes part of the genome inherited by viable progeny. ERVs that colonized ancestral lineages are fixed in contemporary species. However, in some extant species, ERV colonization is ongoing, which results in variation in ERV frequency in the population. To study the consequences of ERV colonization of a host genome, methods are needed to assign each ERV to a location in a species’ genome and determine which individuals have acquired each ERV by descent. Because well annotated reference genomes are not widely available for all species, de novo clustering approaches provide an alternative to reference mapping that are insensitive to differences between query and reference and that are amenable to mobile element studies in both model and non-model organisms. However, there is substantial uncertainty in both identifying ERV genomic position and assigning each unique ERV integration site to individuals in a population. We present an analysis suitable for detecting ERV integration sites in species without the need for a reference genome. Our approach is based on improved de novo clustering methods and statistical models that take the uncertainty of assignment into account and yield a probability matrix of shared ERV integration sites among individuals. We demonstrate that polymorphic integrations of a recently identified endogenous retrovirus in deer reflect contemporary relationships among individuals and populations.

  13. Statistics

    International Nuclear Information System (INIS)

    2005-01-01

    For the years 2004 and 2005 the figures shown in the tables of Energy Review are partly preliminary. The annual statistics published in Energy Review are presented in more detail in a publication called Energy Statistics that comes out yearly. Energy Statistics also includes historical time-series over a longer period of time (see e.g. Energy Statistics, Statistics Finland, Helsinki 2004.) The applied energy units and conversion coefficients are shown in the back cover of the Review. Explanatory notes to the statistical tables can be found after tables and figures. The figures presents: Changes in GDP, energy consumption and electricity consumption, Carbon dioxide emissions from fossile fuels use, Coal consumption, Consumption of natural gas, Peat consumption, Domestic oil deliveries, Import prices of oil, Consumer prices of principal oil products, Fuel prices in heat production, Fuel prices in electricity production, Price of electricity by type of consumer, Average monthly spot prices at the Nord pool power exchange, Total energy consumption by source and CO 2 -emissions, Supplies and total consumption of electricity GWh, Energy imports by country of origin in January-June 2003, Energy exports by recipient country in January-June 2003, Consumer prices of liquid fuels, Consumer prices of hard coal, natural gas and indigenous fuels, Price of natural gas by type of consumer, Price of electricity by type of consumer, Price of district heating by type of consumer, Excise taxes, value added taxes and fiscal charges and fees included in consumer prices of some energy sources and Energy taxes, precautionary stock fees and oil pollution fees

  14. A multi-criteria evaluation system for marine litter pollution based on statistical analyses of OSPAR beach litter monitoring time series.

    Science.gov (United States)

    Schulz, Marcus; Neumann, Daniel; Fleet, David M; Matthies, Michael

    2013-12-01

    During the last decades, marine pollution with anthropogenic litter has become a worldwide major environmental concern. Standardized monitoring of litter since 2001 on 78 beaches selected within the framework of the Convention for the Protection of the Marine Environment of the North-East Atlantic (OSPAR) has been used to identify temporal trends of marine litter. Based on statistical analyses of this dataset a two-part multi-criteria evaluation system for beach litter pollution of the North-East Atlantic and the North Sea is proposed. Canonical correlation analyses, linear regression analyses, and non-parametric analyses of variance were used to identify different temporal trends. A classification of beaches was derived from cluster analyses and served to define different states of beach quality according to abundances of 17 input variables. The evaluation system is easily applicable and relies on the above-mentioned classification and on significant temporal trends implied by significant rank correlations. Copyright © 2013 Elsevier Ltd. All rights reserved.

  15. Statistics

    International Nuclear Information System (INIS)

    2001-01-01

    For the year 2000, part of the figures shown in the tables of the Energy Review are preliminary or estimated. The annual statistics of the Energy Review appear in more detail from the publication Energiatilastot - Energy Statistics issued annually, which also includes historical time series over a longer period (see e.g. Energiatilastot 1999, Statistics Finland, Helsinki 2000, ISSN 0785-3165). The inside of the Review's back cover shows the energy units and the conversion coefficients used for them. Explanatory notes to the statistical tables can be found after tables and figures. The figures presents: Changes in the volume of GNP and energy consumption, Changes in the volume of GNP and electricity, Coal consumption, Natural gas consumption, Peat consumption, Domestic oil deliveries, Import prices of oil, Consumer prices of principal oil products, Fuel prices for heat production, Fuel prices for electricity production, Carbon dioxide emissions from the use of fossil fuels, Total energy consumption by source and CO 2 -emissions, Electricity supply, Energy imports by country of origin in 2000, Energy exports by recipient country in 2000, Consumer prices of liquid fuels, Consumer prices of hard coal, natural gas and indigenous fuels, Average electricity price by type of consumer, Price of district heating by type of consumer, Excise taxes, value added taxes and fiscal charges and fees included in consumer prices of some energy sources and Energy taxes and precautionary stock fees on oil products

  16. Statistics

    International Nuclear Information System (INIS)

    2000-01-01

    For the year 1999 and 2000, part of the figures shown in the tables of the Energy Review are preliminary or estimated. The annual statistics of the Energy Review appear in more detail from the publication Energiatilastot - Energy Statistics issued annually, which also includes historical time series over a longer period (see e.g., Energiatilastot 1998, Statistics Finland, Helsinki 1999, ISSN 0785-3165). The inside of the Review's back cover shows the energy units and the conversion coefficients used for them. Explanatory notes to the statistical tables can be found after tables and figures. The figures presents: Changes in the volume of GNP and energy consumption, Changes in the volume of GNP and electricity, Coal consumption, Natural gas consumption, Peat consumption, Domestic oil deliveries, Import prices of oil, Consumer prices of principal oil products, Fuel prices for heat production, Fuel prices for electricity production, Carbon dioxide emissions, Total energy consumption by source and CO 2 -emissions, Electricity supply, Energy imports by country of origin in January-March 2000, Energy exports by recipient country in January-March 2000, Consumer prices of liquid fuels, Consumer prices of hard coal, natural gas and indigenous fuels, Average electricity price by type of consumer, Price of district heating by type of consumer, Excise taxes, value added taxes and fiscal charges and fees included in consumer prices of some energy sources and Energy taxes and precautionary stock fees on oil products

  17. Statistics

    International Nuclear Information System (INIS)

    1999-01-01

    For the year 1998 and the year 1999, part of the figures shown in the tables of the Energy Review are preliminary or estimated. The annual statistics of the Energy Review appear in more detail from the publication Energiatilastot - Energy Statistics issued annually, which also includes historical time series over a longer period (see e.g. Energiatilastot 1998, Statistics Finland, Helsinki 1999, ISSN 0785-3165). The inside of the Review's back cover shows the energy units and the conversion coefficients used for them. Explanatory notes to the statistical tables can be found after tables and figures. The figures presents: Changes in the volume of GNP and energy consumption, Changes in the volume of GNP and electricity, Coal consumption, Natural gas consumption, Peat consumption, Domestic oil deliveries, Import prices of oil, Consumer prices of principal oil products, Fuel prices for heat production, Fuel prices for electricity production, Carbon dioxide emissions, Total energy consumption by source and CO 2 -emissions, Electricity supply, Energy imports by country of origin in January-June 1999, Energy exports by recipient country in January-June 1999, Consumer prices of liquid fuels, Consumer prices of hard coal, natural gas and indigenous fuels, Average electricity price by type of consumer, Price of district heating by type of consumer, Excise taxes, value added taxes and fiscal charges and fees included in consumer prices of some energy sources and Energy taxes and precautionary stock fees on oil products

  18. Identifying individuality and variability in team tactics by means of statistical shape analysis and multilayer perceptrons.

    Science.gov (United States)

    Jäger, Jörg M; Schöllhorn, Wolfgang I

    2012-04-01

    Offensive and defensive systems of play represent important aspects of team sports. They include the players' positions at certain situations during a match, i.e., when players have to be on specific positions on the court. Patterns of play emerge based on the formations of the players on the court. Recognition of these patterns is important to react adequately and to adjust own strategies to the opponent. Furthermore, the ability to apply variable patterns of play seems to be promising since they make it harder for the opponent to adjust. The purpose of this study is to identify different team tactical patterns in volleyball and to analyze differences in variability. Overall 120 standard situations of six national teams in women's volleyball are analyzed during a world championship tournament. Twenty situations from each national team are chosen, including the base defence position (start configuration) and the two players block with middle back deep (end configuration). The shapes of the defence formations at the start and end configurations during the defence of each national team as well as the variability of these defence formations are statistically analyzed. Furthermore these shapes data are used to train multilayer perceptrons in order to test whether artificial neural networks can recognize the teams by their tactical patterns. Results show significant differences between the national teams in both the base defence position at the start and the two players block with middle back deep at the end of the standard defence situation. Furthermore, the national teams show significant differences in variability of the defence systems and start-positions are more variable than the end-positions. Multilayer perceptrons are able to recognize the teams at an average of 98.5%. It is concluded that defence systems in team sports are highly individual at a competitive level and variable even in standard situations. Artificial neural networks can be used to recognize

  19. Analysing the Severity and Frequency of Traffic Crashes in Riyadh City Using Statistical Models

    Directory of Open Access Journals (Sweden)

    Saleh Altwaijri

    2012-12-01

    Full Text Available Traffic crashes in Riyadh city cause losses in the form of deaths, injuries and property damages, in addition to the pain and social tragedy affecting families of the victims. In 2005, there were a total of 47,341 injury traffic crashes occurred in Riyadh city (19% of the total KSA crashes and 9% of those crashes were severe. Road safety in Riyadh city may have been adversely affected by: high car ownership, migration of people to Riyadh city, high daily trips reached about 6 million, high rate of income, low-cost of petrol, drivers from different nationalities, young drivers and tremendous growth in population which creates a high level of mobility and transport activities in the city. The primary objective of this paper is therefore to explore factors affecting the severity and frequency of road crashes in Riyadh city using appropriate statistical models aiming to establish effective safety policies ready to be implemented to reduce the severity and frequency of road crashes in Riyadh city. Crash data for Riyadh city were collected from the Higher Commission for the Development of Riyadh (HCDR for a period of five years from 1425H to 1429H (roughly corresponding to 2004-2008. Crash data were classified into three categories: fatal, serious-injury and slight-injury. Two nominal response models have been developed: a standard multinomial logit model (MNL and a mixed logit model to injury-related crash data. Due to a severe underreporting problem on the slight injury crashes binary and mixed binary logistic regression models were also estimated for two categories of severity: fatal and serious crashes. For frequency, two count models such as Negative Binomial (NB models were employed and the unit of analysis was 168 HAIs (wards in Riyadh city. Ward-level crash data are disaggregated by severity of the crash (such as fatal and serious injury crashes. The results from both multinomial and binary response models are found to be fairly consistent but

  20. Cardiac arrhythmia detection using combination of heart rate variability analyses and PUCK analysis.

    Science.gov (United States)

    Mahananto, Faizal; Igasaki, Tomohiko; Murayama, Nobuki

    2013-01-01

    This paper presents cardiac arrhythmia detection using the combination of a heart rate variability (HRV) analysis and a "potential of unbalanced complex kinetics" (PUCK) analysis. Detection performance was improved by adding features extracted from the PUCK analysis. Initially, R-R interval data were extracted from the original electrocardiogram (ECG) recordings and were cut into small segments and marked as either normal or arrhythmia. HRV analyses then were conducted using the segmented R-R interval data, including a time-domain analysis, frequency-domain analysis, and nonlinear analysis. In addition to the HRV analysis, PUCK analysis, which has been implemented successfully in a foreign exchange market series to characterize change, was employed. A decision-tree algorithm was applied to all of the obtained features for classification. The proposed method was tested using the MIT-BIH arrhythmia database and had an overall classification accuracy of 91.73%. After combining features obtained from the PUCK analysis, the overall accuracy increased to 92.91%. Therefore, we suggest that the use of a PUCK analysis in conjunction with HRV analysis might improve performance accuracy for the detection of cardiac arrhythmia.

  1. Robust Machine Learning Variable Importance Analyses of Medical Conditions for Health Care Spending.

    Science.gov (United States)

    Rose, Sherri

    2018-03-11

    To propose nonparametric double robust machine learning in variable importance analyses of medical conditions for health spending. 2011-2012 Truven MarketScan database. I evaluate how much more, on average, commercially insured enrollees with each of 26 of the most prevalent medical conditions cost per year after controlling for demographics and other medical conditions. This is accomplished within the nonparametric targeted learning framework, which incorporates ensemble machine learning. Previous literature studying the impact of medical conditions on health care spending has almost exclusively focused on parametric risk adjustment; thus, I compare my approach to parametric regression. My results demonstrate that multiple sclerosis, congestive heart failure, severe cancers, major depression and bipolar disorders, and chronic hepatitis are the most costly medical conditions on average per individual. These findings differed from those obtained using parametric regression. The literature may be underestimating the spending contributions of several medical conditions, which is a potentially critical oversight. If current methods are not capturing the true incremental effect of medical conditions, undesirable incentives related to care may remain. Further work is needed to directly study these issues in the context of federal formulas. © Health Research and Educational Trust.

  2. Statistics

    International Nuclear Information System (INIS)

    2003-01-01

    For the year 2002, part of the figures shown in the tables of the Energy Review are partly preliminary. The annual statistics of the Energy Review also includes historical time-series over a longer period (see e.g. Energiatilastot 2001, Statistics Finland, Helsinki 2002). The applied energy units and conversion coefficients are shown in the inside back cover of the Review. Explanatory notes to the statistical tables can be found after tables and figures. The figures presents: Changes in GDP, energy consumption and electricity consumption, Carbon dioxide emissions from fossile fuels use, Coal consumption, Consumption of natural gas, Peat consumption, Domestic oil deliveries, Import prices of oil, Consumer prices of principal oil products, Fuel prices in heat production, Fuel prices in electricity production, Price of electricity by type of consumer, Average monthly spot prices at the Nord pool power exchange, Total energy consumption by source and CO 2 -emissions, Supply and total consumption of electricity GWh, Energy imports by country of origin in January-June 2003, Energy exports by recipient country in January-June 2003, Consumer prices of liquid fuels, Consumer prices of hard coal, natural gas and indigenous fuels, Price of natural gas by type of consumer, Price of electricity by type of consumer, Price of district heating by type of consumer, Excise taxes, value added taxes and fiscal charges and fees included in consumer prices of some energy sources and Excise taxes, precautionary stock fees on oil pollution fees on energy products

  3. Statistics

    International Nuclear Information System (INIS)

    2004-01-01

    For the year 2003 and 2004, the figures shown in the tables of the Energy Review are partly preliminary. The annual statistics of the Energy Review also includes historical time-series over a longer period (see e.g. Energiatilastot, Statistics Finland, Helsinki 2003, ISSN 0785-3165). The applied energy units and conversion coefficients are shown in the inside back cover of the Review. Explanatory notes to the statistical tables can be found after tables and figures. The figures presents: Changes in GDP, energy consumption and electricity consumption, Carbon dioxide emissions from fossile fuels use, Coal consumption, Consumption of natural gas, Peat consumption, Domestic oil deliveries, Import prices of oil, Consumer prices of principal oil products, Fuel prices in heat production, Fuel prices in electricity production, Price of electricity by type of consumer, Average monthly spot prices at the Nord pool power exchange, Total energy consumption by source and CO 2 -emissions, Supplies and total consumption of electricity GWh, Energy imports by country of origin in January-March 2004, Energy exports by recipient country in January-March 2004, Consumer prices of liquid fuels, Consumer prices of hard coal, natural gas and indigenous fuels, Price of natural gas by type of consumer, Price of electricity by type of consumer, Price of district heating by type of consumer, Excise taxes, value added taxes and fiscal charges and fees included in consumer prices of some energy sources and Excise taxes, precautionary stock fees on oil pollution fees

  4. Statistics

    International Nuclear Information System (INIS)

    2000-01-01

    For the year 1999 and 2000, part of the figures shown in the tables of the Energy Review are preliminary or estimated. The annual statistics of the Energy also includes historical time series over a longer period (see e.g., Energiatilastot 1999, Statistics Finland, Helsinki 2000, ISSN 0785-3165). The inside of the Review's back cover shows the energy units and the conversion coefficients used for them. Explanatory notes to the statistical tables can be found after tables and figures. The figures presents: Changes in the volume of GNP and energy consumption, Changes in the volume of GNP and electricity, Coal consumption, Natural gas consumption, Peat consumption, Domestic oil deliveries, Import prices of oil, Consumer prices of principal oil products, Fuel prices for heat production, Fuel prices for electricity production, Carbon dioxide emissions, Total energy consumption by source and CO 2 -emissions, Electricity supply, Energy imports by country of origin in January-June 2000, Energy exports by recipient country in January-June 2000, Consumer prices of liquid fuels, Consumer prices of hard coal, natural gas and indigenous fuels, Average electricity price by type of consumer, Price of district heating by type of consumer, Excise taxes, value added taxes and fiscal charges and fees included in consumer prices of some energy sources and Energy taxes and precautionary stock fees on oil products

  5. Does bisphenol A induce superfeminization in Marisa cornuarietis? Part II: toxicity test results and requirements for statistical power analyses.

    Science.gov (United States)

    Forbes, Valery E; Aufderheide, John; Warbritton, Ryan; van der Hoeven, Nelly; Caspers, Norbert

    2007-03-01

    This study presents results of the effects of bisphenol A (BPA) on adult egg production, egg hatchability, egg development rates and juvenile growth rates in the freshwater gastropod, Marisa cornuarietis. We observed no adult mortality, substantial inter-snail variability in reproductive output, and no effects of BPA on reproduction during 12 weeks of exposure to 0, 0.1, 1.0, 16, 160 or 640 microg/L BPA. We observed no effects of BPA on egg hatchability or timing of egg hatching. Juveniles showed good growth in the control and all treatments, and there were no significant effects of BPA on this endpoint. Our results do not support previous claims of enhanced reproduction in Marisa cornuarietis in response to exposure to BPA. Statistical power analysis indicated high levels of inter-snail variability in the measured endpoints and highlighted the need for sufficient replication when testing treatment effects on reproduction in M. cornuarietis with adequate power.

  6. Statistical evaluation of variables affecting occurrence of hydrocarbons in aquifers used for public supply, California

    Science.gov (United States)

    Landon, Matthew K.; Burton, Carmen A.; Davis, Tracy A.; Belitz, Kenneth; Johnson, Tyler D.

    2014-01-01

    The variables affecting the occurrence of hydrocarbons in aquifers used for public supply in California were assessed based on statistical evaluation of three large statewide datasets; gasoline oxygenates also were analyzed for comparison with hydrocarbons. Benzene is the most frequently detected (1.7%) compound among 17 hydrocarbons analyzed at generally low concentrations (median detected concentration 0.024 μg/l) in groundwater used for public supply in California; methyl tert-butyl ether (MTBE) is the most frequently detected (5.8%) compound among seven oxygenates analyzed (median detected concentration 0.1 μg/l). At aquifer depths used for public supply, hydrocarbons and MTBE rarely co-occur and are generally related to different variables; in shallower groundwater, co-occurrence is more frequent and there are similar relations to the density or proximity of potential sources. Benzene concentrations are most strongly correlated with reducing conditions, regardless of groundwater age and depth. Multiple lines of evidence indicate that benzene and other hydrocarbons detected in old, deep, and/or brackish groundwater result from geogenic sources of oil and gas. However, in recently recharged (since ~1950), generally shallower groundwater, higher concentrations and detection frequencies of benzene and hydrocarbons were associated with a greater proportion of commercial land use surrounding the well, likely reflecting effects of anthropogenic sources, particularly in combination with reducing conditions.

  7. Multivariate statistical analysis of radioactive variables in two phosphate ores from Sudan

    International Nuclear Information System (INIS)

    Adam, Abdel Majid A.; Eltayeb, Mohamed Ahmed H.

    2012-01-01

    Multivariate statistical techniques are efficient ways to display complex relationships among many objects. An attempt was made to study the radioactive data in two types of Sudanese phosphate deposits; Kurun and Uro phosphate, using several multivariate statistical methods. Pearson correlation coefficient revealed that a U-238 distribution in Kurun phosphate is controlled by the variation of K-40 concentration, whereas in Uro phosphate it is controlled by the variation of U-235 and U-234 concentration. Histograms and normal Q–Q plots clearly show that the radioactive variables did not follow a normal distribution. This non-normality feature observed may be attributed to complicating influence of geological factors. The principal components analysis (PCA) gives a model of five components for representing the acquired data from Kurun phosphate, where 89.5% of the total variance is explained. A model of four components was sufficient to represent the acquired data from Uro phosphate, where 87.5% of the total data variance is explained. The hierarchical cluster analysis (HCA) indicates that U-238 behaves in the same manner in the two types of phosphates; it associated with a group of four radionuclides; U-234, Po-210, Ra-226, Th-230, which the most abundant radionuclides, and all belong to the uranium-238 decay series. Two parameters have been adapted for the direct differentiate between the two phosphates. Firstly, U-238 in Uro phosphate have shown higher degree of mobility (CV% = 82.6) than that in Kurun phosphate (CV% = 64.7), and secondly, the activity ratio of Th-230/Th-232 in Uro phosphate is nine times than that in Kurun phosphate. - Highlights: ► Multivariate statistical techniques were used to characterize radioactive data. ► U-238 in Uro phosphate shows higher degree of mobility (CV% = 82.6). ► U-238 in Kurun phosphate shows lower degree of mobility (CV% = 64.7). ► The radioactive variables did not follow a normal distribution. ► The ratio of Th

  8. Linking GPS Telemetry Surveys and Scat Analyses Helps Explain Variability in Black Bear Foraging Strategies.

    Science.gov (United States)

    Lesmerises, Rémi; Rebouillat, Lucie; Dussault, Claude; St-Laurent, Martin-Hugues

    2015-01-01

    Studying diet is fundamental to animal ecology and scat analysis, a widespread approach, is considered a reliable dietary proxy. Nonetheless, this method has weaknesses such as non-random sampling of habitats and individuals, inaccurate evaluation of excretion date, and lack of assessment of inter-individual dietary variability. We coupled GPS telemetry and scat analyses of black bears Ursus americanus Pallas to relate diet to individual characteristics and habitat use patterns while foraging. We captured 20 black bears (6 males and 14 females) and fitted them with GPS/Argos collars. We then surveyed GPS locations shortly after individual bear visits and collected 139 feces in 71 different locations. Fecal content (relative dry matter biomass of ingested items) was subsequently linked to individual characteristics (sex, age, reproductive status) and to habitats visited during foraging bouts using Brownian bridges based on GPS locations prior to feces excretion. At the population level, diet composition was similar to what was previously described in studies on black bears. However, our individual-based method allowed us to highlight different intra-population patterns, showing that sex and female reproductive status had significant influence on individual diet. For example, in the same habitats, females with cubs did not use the same food sources as lone bears. Linking fecal content (i.e., food sources) to habitat previously visited by different individuals, we demonstrated a potential differential use of similar habitats dependent on individual characteristics. Females with cubs-of-the-year tended to use old forest clearcuts (6-20 years old) to feed on bunchberry, whereas females with yearling foraged for blueberry and lone bears for ants. Coupling GPS telemetry and scat analyses allows for efficient detection of inter-individual or inter-group variations in foraging strategies and of linkages between previous habitat use and food consumption, even for cryptic

  9. Linking GPS Telemetry Surveys and Scat Analyses Helps Explain Variability in Black Bear Foraging Strategies.

    Directory of Open Access Journals (Sweden)

    Rémi Lesmerises

    Full Text Available Studying diet is fundamental to animal ecology and scat analysis, a widespread approach, is considered a reliable dietary proxy. Nonetheless, this method has weaknesses such as non-random sampling of habitats and individuals, inaccurate evaluation of excretion date, and lack of assessment of inter-individual dietary variability. We coupled GPS telemetry and scat analyses of black bears Ursus americanus Pallas to relate diet to individual characteristics and habitat use patterns while foraging. We captured 20 black bears (6 males and 14 females and fitted them with GPS/Argos collars. We then surveyed GPS locations shortly after individual bear visits and collected 139 feces in 71 different locations. Fecal content (relative dry matter biomass of ingested items was subsequently linked to individual characteristics (sex, age, reproductive status and to habitats visited during foraging bouts using Brownian bridges based on GPS locations prior to feces excretion. At the population level, diet composition was similar to what was previously described in studies on black bears. However, our individual-based method allowed us to highlight different intra-population patterns, showing that sex and female reproductive status had significant influence on individual diet. For example, in the same habitats, females with cubs did not use the same food sources as lone bears. Linking fecal content (i.e., food sources to habitat previously visited by different individuals, we demonstrated a potential differential use of similar habitats dependent on individual characteristics. Females with cubs-of-the-year tended to use old forest clearcuts (6-20 years old to feed on bunchberry, whereas females with yearling foraged for blueberry and lone bears for ants. Coupling GPS telemetry and scat analyses allows for efficient detection of inter-individual or inter-group variations in foraging strategies and of linkages between previous habitat use and food consumption, even

  10. Energetic and exergetic analyses of a variable compression ratio spark ignition gas engine

    International Nuclear Information System (INIS)

    Javaheri, A.; Esfahanian, V.; Salavati-Zadeh, A.; Darzi, M.

    2014-01-01

    Highlights: • Effects of CR and λ on CNG SI ICE 1st and 2nd law analyses are experimentally studied. • The performance of pure methane and a real CNG are observed and compared. • The ratio of actual to Otto cycle thermal efficiencies is 0.78 for all cases. • At least 25.5% of destructed availability is due to combustion irreversibility. • With decrease in methane content, CNG shows more combustion irreversibility. - Abstract: Considering the significance of obtaining higher efficiencies from internal combustion engines (ICE) along with the growing role of natural gas as a fuel, the present work is set to explore the effects of compression ratio (CR hereafter) and air/fuel equivalence ratio (AFER hereafter) on the energy and exergy potentials in a gas-fueled spark ignition internal combustion engine. Experiments are carried out using a single cylinder, port injection, water cooled, variable compression ratio (VCR hereafter), spark ignition engine at a constant engine speed of 2000 rpm. The study involves CRs of 12, 14 and 16 and 10 AFERs between 0.8 and 1.25. Pure methane is utilized for the analysis. In addition, a natural gas blend with the minimum methane content among Iranian gas sources is also tested in order to investigate the effect of real natural gas on findings. The energy analysis involves input fuel power, indicated power and losses due to high temperature of exhaust gases and their unburned content, blow-by and heat loss. The exergy analysis is carried out for availability input and piston, exhaust, and losses availabilities along with destructed entropy. The analysis indicates an increase in the ratio of thermo-mechanical exhaust availability to fuel availability by CR with a maximum near stoichiometry, whereas it is shown that chemical exhaust exergy is not dependent on CR and reduces with AFER. In addition, it is indicated that the ratio of actual cycle to Otto cycle thermal efficiencies is about constant (about 0.784) with changing CR

  11. Analysis of the interannual variability of tropical cyclones striking the California coast based on statistical downscaling

    Science.gov (United States)

    Mendez, F. J.; Rueda, A.; Barnard, P.; Mori, N.; Nakajo, S.; Espejo, A.; del Jesus, M.; Diez Sierra, J.; Cofino, A. S.; Camus, P.

    2016-02-01

    Hurricanes hitting California have a very low ocurrence probability due to typically cool ocean temperature and westward tracks. However, damages associated to these improbable events would be dramatic in Southern California and understanding the oceanographic and atmospheric drivers is of paramount importance for coastal risk management for present and future climates. A statistical analysis of the historical events is very difficult due to the limited resolution of atmospheric and oceanographic forcing data available. In this work, we propose a combination of: (a) statistical downscaling methods (Espejo et al, 2015); and (b) a synthetic stochastic tropical cyclone (TC) model (Nakajo et al, 2014). To build the statistical downscaling model, Y=f(X), we apply a combination of principal component analysis and the k-means classification algorithm to find representative patterns from a potential TC index derived from large-scale SST fields in Eastern Central Pacific (predictor X) and the associated tropical cyclone ocurrence (predictand Y). SST data comes from NOAA Extended Reconstructed SST V3b providing information from 1854 to 2013 on a 2.0 degree x 2.0 degree global grid. As data for the historical occurrence and paths of tropical cycloneas are scarce, we apply a stochastic TC model which is based on a Monte Carlo simulation of the joint distribution of track, minimum sea level pressure and translation speed of the historical events in the Eastern Central Pacific Ocean. Results will show the ability of the approach to explain seasonal-to-interannual variability of the predictor X, which is clearly related to El Niño Southern Oscillation. References Espejo, A., Méndez, F.J., Diez, J., Medina, R., Al-Yahyai, S. (2015) Seasonal probabilistic forecasting of tropical cyclone activity in the North Indian Ocean, Journal of Flood Risk Management, DOI: 10.1111/jfr3.12197 Nakajo, S., N. Mori, T. Yasuda, and H. Mase (2014) Global Stochastic Tropical Cyclone Model Based on

  12. A Stochastic Model of Space-Time Variability of Tropical Rainfall: I. Statistics of Spatial Averages

    Science.gov (United States)

    Kundu, Prasun K.; Bell, Thomas L.; Lau, William K. M. (Technical Monitor)

    2002-01-01

    Global maps of rainfall are of great importance in connection with modeling of the earth s climate. Comparison between the maps of rainfall predicted by computer-generated climate models with observation provides a sensitive test for these models. To make such a comparison, one typically needs the total precipitation amount over a large area, which could be hundreds of kilometers in size over extended periods of time of order days or months. This presents a difficult problem since rain varies greatly from place to place as well as in time. Remote sensing methods using ground radar or satellites detect rain over a large area by essentially taking a series of snapshots at infrequent intervals and indirectly deriving the average rain intensity within a collection of pixels , usually several kilometers in size. They measure area average of rain at a particular instant. Rain gauges, on the other hand, record rain accumulation continuously in time but only over a very small area tens of centimeters across, say, the size of a dinner plate. They measure only a time average at a single location. In making use of either method one needs to fill in the gaps in the observation - either the gaps in the area covered or the gaps in time of observation. This involves using statistical models to obtain information about the rain that is missed from what is actually detected. This paper investigates such a statistical model and validates it with rain data collected over the tropical Western Pacific from ship borne radars during TOGA COARE (Tropical Oceans Global Atmosphere Coupled Ocean-Atmosphere Response Experiment). The model incorporates a number of commonly observed features of rain. While rain varies rapidly with location and time, the variability diminishes when averaged over larger areas or longer periods of time. Moreover, rain is patchy in nature - at any instant on the average only a certain fraction of the observed pixels contain rain. The fraction of area covered by

  13. The number of subjects per variable required in linear regression analyses

    NARCIS (Netherlands)

    P.C. Austin (Peter); E.W. Steyerberg (Ewout)

    2015-01-01

    textabstractObjectives To determine the number of independent variables that can be included in a linear regression model. Study Design and Setting We used a series of Monte Carlo simulations to examine the impact of the number of subjects per variable (SPV) on the accuracy of estimated regression

  14. Statistical Modeling Approach to Quantitative Analysis of Interobserver Variability in Breast Contouring

    Energy Technology Data Exchange (ETDEWEB)

    Yang, Jinzhong, E-mail: jyang4@mdanderson.org [Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas (United States); Woodward, Wendy A.; Reed, Valerie K.; Strom, Eric A.; Perkins, George H.; Tereffe, Welela; Buchholz, Thomas A. [Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas (United States); Zhang, Lifei; Balter, Peter; Court, Laurence E. [Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas (United States); Li, X. Allen [Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, Wisconsin (United States); Dong, Lei [Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas (United States); Scripps Proton Therapy Center, San Diego, California (United States)

    2014-05-01

    Purpose: To develop a new approach for interobserver variability analysis. Methods and Materials: Eight radiation oncologists specializing in breast cancer radiation therapy delineated a patient's left breast “from scratch” and from a template that was generated using deformable image registration. Three of the radiation oncologists had previously received training in Radiation Therapy Oncology Group consensus contouring for breast cancer atlas. The simultaneous truth and performance level estimation algorithm was applied to the 8 contours delineated “from scratch” to produce a group consensus contour. Individual Jaccard scores were fitted to a beta distribution model. We also applied this analysis to 2 or more patients, which were contoured by 9 breast radiation oncologists from 8 institutions. Results: The beta distribution model had a mean of 86.2%, standard deviation (SD) of ±5.9%, a skewness of −0.7, and excess kurtosis of 0.55, exemplifying broad interobserver variability. The 3 RTOG-trained physicians had higher agreement scores than average, indicating that their contours were close to the group consensus contour. One physician had high sensitivity but lower specificity than the others, which implies that this physician tended to contour a structure larger than those of the others. Two other physicians had low sensitivity but specificity similar to the others, which implies that they tended to contour a structure smaller than the others. With this information, they could adjust their contouring practice to be more consistent with others if desired. When contouring from the template, the beta distribution model had a mean of 92.3%, SD ± 3.4%, skewness of −0.79, and excess kurtosis of 0.83, which indicated a much better consistency among individual contours. Similar results were obtained for the analysis of 2 additional patients. Conclusions: The proposed statistical approach was able to measure interobserver variability quantitatively

  15. Sea Surface Height Variability and Eddy Statistical Properties in the Red Sea

    KAUST Repository

    Zhan, Peng

    2013-05-01

    Satellite sea surface height (SSH) data over 1992-2012 are analyzed to study the spatial and temporal variability of sea level in the Red Sea. Empirical orthogonal functions (EOF) analysis suggests the remarkable seasonality of SSH in the Red Sea, and a significant correlation is found between SSH variation and seasonal wind cycle. A winding-angle based eddy identification algorithm is employed to derive the mesoscale eddy information from SSH data. Totally more than 5500 eddies are detected, belonging to 2583 eddy tracks. Statistics suggest that eddies generate over the entire Red Sea, with two regions in the central basin of high eddy frequency. 76% of the detected eddies have a radius ranging from 40km to 100km, of which both intensity and absolute vorticity decrease with eddy radius. The average eddy lifespan is about 5 weeks, and eddies with longer lifespan tend to have larger radius but less intensity. Different deformation rate exists between anticyclonic eddies (AEs) and cyclonic eddies (CEs), those eddies with higher intensity appear to be less deformed and more circular. Inspection of the 84 long-lived eddies suggests the AEs tend to move a little more northward than CEs. AE generation during summer is obviously lower than that during other seasons, while CE generation is higher during spring and summer. Other features of AEs and CEs are similar with both vorticity and intensity reaching the summer peaks in August and winter peaks in January. Inter-annual variability reveals that the eddies in the Red Sea are isolated from the global event. The eddy property tendencies are different from the south and north basin, both of which exhibit a two-year cycle. Showing a correlation coefficient of -0.91, Brunt–Väisälä frequency is negatively correlated with eddy kinetic energy (EKE), which results from AE activities in the high eddy frequency region. Climatological vertical velocity shear variation is identical with EKE except in the autumn, suggesting the

  16. Digital immunohistochemistry platform for the staining variation monitoring based on integration of image and statistical analyses with laboratory information system.

    Science.gov (United States)

    Laurinaviciene, Aida; Plancoulaine, Benoit; Baltrusaityte, Indra; Meskauskas, Raimundas; Besusparis, Justinas; Lesciute-Krilaviciene, Daiva; Raudeliunas, Darius; Iqbal, Yasir; Herlin, Paulette; Laurinavicius, Arvydas

    2014-01-01

    Digital immunohistochemistry (IHC) is one of the most promising applications brought by new generation image analysis (IA). While conventional IHC staining quality is monitored by semi-quantitative visual evaluation of tissue controls, IA may require more sensitive measurement. We designed an automated system to digitally monitor IHC multi-tissue controls, based on SQL-level integration of laboratory information system with image and statistical analysis tools. Consecutive sections of TMA containing 10 cores of breast cancer tissue were used as tissue controls in routine Ki67 IHC testing. Ventana slide label barcode ID was sent to the LIS to register the serial section sequence. The slides were stained and scanned (Aperio ScanScope XT), IA was performed by the Aperio/Leica Colocalization and Genie Classifier/Nuclear algorithms. SQL-based integration ensured automated statistical analysis of the IA data by the SAS Enterprise Guide project. Factor analysis and plot visualizations were performed to explore slide-to-slide variation of the Ki67 IHC staining results in the control tissue. Slide-to-slide intra-core IHC staining analysis revealed rather significant variation of the variables reflecting the sample size, while Brown and Blue Intensity were relatively stable. To further investigate this variation, the IA results from the 10 cores were aggregated to minimize tissue-related variance. Factor analysis revealed association between the variables reflecting the sample size detected by IA and Blue Intensity. Since the main feature to be extracted from the tissue controls was staining intensity, we further explored the variation of the intensity variables in the individual cores. MeanBrownBlue Intensity ((Brown+Blue)/2) and DiffBrownBlue Intensity (Brown-Blue) were introduced to better contrast the absolute intensity and the colour balance variation in each core; relevant factor scores were extracted. Finally, tissue-related factors of IHC staining variance were

  17. Variability in source sediment contributions by applying different statistic test for a Pyrenean catchment.

    Science.gov (United States)

    Palazón, L; Navas, A

    2017-06-01

    Information on sediment contribution and transport dynamics from the contributing catchments is needed to develop management plans to tackle environmental problems related with effects of fine sediment as reservoir siltation. In this respect, the fingerprinting technique is an indirect technique known to be valuable and effective for sediment source identification in river catchments. Large variability in sediment delivery was found in previous studies in the Barasona catchment (1509 km 2 , Central Spanish Pyrenees). Simulation results with SWAT and fingerprinting approaches identified badlands and agricultural uses as the main contributors to sediment supply in the reservoir. In this study the Kruskal-Wallis H-test and (3) principal components analysis. Source contribution results were different between assessed options with the greatest differences observed for option using #3, including the two step process: principal components analysis and discriminant function analysis. The characteristics of the solutions by the applied mixing model and the conceptual understanding of the catchment showed that the most reliable solution was achieved using #2, the two step process of Kruskal-Wallis H-test and discriminant function analysis. The assessment showed the importance of the statistical procedure used to define the optimum composite fingerprint for sediment fingerprinting applications. Copyright © 2016 Elsevier Ltd. All rights reserved.

  18. Statistical methodology for discrete fracture model - including fracture size, orientation uncertainty together with intensity uncertainty and variability

    International Nuclear Information System (INIS)

    Darcel, C.; Davy, P.; Le Goc, R.; Dreuzy, J.R. de; Bour, O.

    2009-11-01

    Investigations led for several years at Laxemar and Forsmark reveal the large heterogeneity of geological formations and associated fracturing. This project aims at reinforcing the statistical DFN modeling framework adapted to a site scale. This leads therefore to develop quantitative methods of characterization adapted to the nature of fracturing and data availability. We start with the hypothesis that the maximum likelihood DFN model is a power-law model with a density term depending on orientations. This is supported both by literature and specifically here by former analyses of the SKB data. This assumption is nevertheless thoroughly tested by analyzing the fracture trace and lineament maps. Fracture traces range roughly between 0.5 m and 10 m - i e the usual extension of the sample outcrops. Between the raw data and final data used to compute the fracture size distribution from which the size distribution model will arise, several steps are necessary, in order to correct data from finite-size, topographical and sampling effects. More precisely, a particular attention is paid to fracture segmentation status and fracture linkage consistent with the DFN model expected. The fracture scaling trend observed over both sites displays finally a shape parameter k t close to 1.2 with a density term (α 2d ) between 1.4 and 1.8. Only two outcrops clearly display a different trend with k t close to 3 and a density term (α 2d ) between 2 and 3.5. The fracture lineaments spread over the range between 100 meters and a few kilometers. When compared with fracture trace maps, these datasets are already interpreted and the linkage process developed previously has not to be done. Except for the subregional lineament map from Forsmark, lineaments display a clear power-law trend with a shape parameter k t equal to 3 and a density term between 2 and 4.5. The apparent variation in scaling exponent, from the outcrop scale (k t = 1.2) on one side, to the lineament scale (k t = 2) on

  19. Statistical modelling of variability in sediment-water nutrient and oxygen fluxes

    Science.gov (United States)

    Serpetti, Natalia; Witte, Ursula; Heath, Michael

    2016-06-01

    Organic detritus entering, or produced, in the marine environment is re-mineralised to inorganic nutrient in the seafloor sediments. The flux of dissolved inorganic nutrient between the sediment and overlying water column is a key process in the marine ecosystem, which binds the biogeochemical sub-system to the living food web. These fluxes are potentially affected by a wide range of physical and biological factors and disentangling these is a significant challenge. Here we develop a set of General Additive Models (GAM) of nitrate, nitrite, ammonia, phosphate, silicate and oxygen fluxes, based on a year-long campaign of field measurements off the north-east coast of Scotland. We show that sediment grain size, turbidity due to sediment re-suspension, temperature, and biogenic matter content were the key factors affecting oxygen consumption, ammonia and silicate fluxes. However, phosphate fluxes were only related to suspended sediment concentrations, whilst nitrate fluxes showed no clear relationship to any of the expected drivers of change, probably due to the effects of denitrification. Our analyses show that the stoichiometry of nutrient regeneration in the ecosystem is not necessarily constant and may be affected by combinations of processes. We anticipate that our statistical modelling results will form the basis for testing the functionality of process-based mathematical models of whole-sediment biogeochemistry.

  20. A method for calorimetric analysis in variable conditions heating; Methode d'analyse calorimetrique en regime variable

    Energy Technology Data Exchange (ETDEWEB)

    Berthier, G [Commissariat a l' Energie Atomique, Saclay (France). Centre d' Etudes Nucleaires

    1965-07-01

    By the analysis of the thermal transition conditions given by the quenching of a sample in a furnace maintained at a high temperature, it is possible to study the thermal diffusivity of some materials and those of solid state structure transformation on a qualitative as well as a quantitative standpoint. For instance the transformation energy of {alpha}-quartz into {beta}-quartz and the Wigner energy stored within neutron-irradiated beryllium oxide have been measured. (author) [French] L'analyse du regime thermique transitoire, obtenu par la trempe d'un echantillon dans l'enceinte d'un four maintenu a tres haute temperature, peut permettre l'etude de la diffusivite thermique de certains materiaux et celle des transformations structurales en phase solide, tant du point de vue qualitatif que du point de vue quantitatif (mesure de l'energie de transformation du quartz {alpha} en quartz {beta} et determination de l'energie Wigner emmagasinee par l'oxyde de beryllium irradie aux neutrons). (auteur)

  1. Statistical variability and confidence intervals for planar dose QA pass rates

    Energy Technology Data Exchange (ETDEWEB)

    Bailey, Daniel W.; Nelms, Benjamin E.; Attwood, Kristopher; Kumaraswamy, Lalith; Podgorsak, Matthew B. [Department of Physics, State University of New York at Buffalo, Buffalo, New York 14260 (United States) and Department of Radiation Medicine, Roswell Park Cancer Institute, Buffalo, New York 14263 (United States); Canis Lupus LLC, Merrimac, Wisconsin 53561 (United States); Department of Biostatistics, Roswell Park Cancer Institute, Buffalo, New York 14263 (United States); Department of Radiation Medicine, Roswell Park Cancer Institute, Buffalo, New York 14263 (United States); Department of Radiation Medicine, Roswell Park Cancer Institute, Buffalo, New York 14263 (United States); Department of Molecular and Cellular Biophysics and Biochemistry, Roswell Park Cancer Institute, Buffalo, New York 14263 (United States) and Department of Physiology and Biophysics, State University of New York at Buffalo, Buffalo, New York 14214 (United States)

    2011-11-15

    Purpose: The most common metric for comparing measured to calculated dose, such as for pretreatment quality assurance of intensity-modulated photon fields, is a pass rate (%) generated using percent difference (%Diff), distance-to-agreement (DTA), or some combination of the two (e.g., gamma evaluation). For many dosimeters, the grid of analyzed points corresponds to an array with a low areal density of point detectors. In these cases, the pass rates for any given comparison criteria are not absolute but exhibit statistical variability that is a function, in part, on the detector sampling geometry. In this work, the authors analyze the statistics of various methods commonly used to calculate pass rates and propose methods for establishing confidence intervals for pass rates obtained with low-density arrays. Methods: Dose planes were acquired for 25 prostate and 79 head and neck intensity-modulated fields via diode array and electronic portal imaging device (EPID), and matching calculated dose planes were created via a commercial treatment planning system. Pass rates for each dose plane pair (both centered to the beam central axis) were calculated with several common comparison methods: %Diff/DTA composite analysis and gamma evaluation, using absolute dose comparison with both local and global normalization. Specialized software was designed to selectively sample the measured EPID response (very high data density) down to discrete points to simulate low-density measurements. The software was used to realign the simulated detector grid at many simulated positions with respect to the beam central axis, thereby altering the low-density sampled grid. Simulations were repeated with 100 positional iterations using a 1 detector/cm{sup 2} uniform grid, a 2 detector/cm{sup 2} uniform grid, and similar random detector grids. For each simulation, %/DTA composite pass rates were calculated with various %Diff/DTA criteria and for both local and global %Diff normalization

  2. Spectral analyses of systolic blood pressure and heart rate variability and their association with cognitive performance in elderly hypertensive subjects.

    Science.gov (United States)

    Santos, W B; Matoso, J M D; Maltez, M; Gonçalves, T; Casanova, M; Moreira, I F H; Lourenço, R A; Monteiro, W D; Farinatti, P T V; Soares, P P; Oigman, W; Neves, M F T; Correia, M L G

    2015-08-01

    Systolic hypertension is associated with cognitive decline in the elderly. Altered blood pressure (BP) variability is a possible mechanism of reduced cognitive performance in elderly hypertensives. We hypothesized that altered beat-to-beat systolic BP variability is associated with reduced global cognitive performance in elderly hypertensive subjects. In exploratory analyses, we also studied the correlation between diverse discrete cognitive domains and indices of systolic BP and heart rate variability. Disproving our initial hypothesis, we have shown that hypertension and low education, but not indices of systolic BP and heart rate variability, were independent predictors of lower global cognitive performance. However, exploratory analyses showed that the systolic BP variability in semi-upright position was an independent predictor of matrix reasoning (B = 0.08 ± .03, P-value = 0.005), whereas heart rate variability in semi-upright position was an independent predictor of the executive function score (B = -6.36 ± 2.55, P-value = 0.02). We conclude that myogenic vascular and sympathetic modulation of systolic BP do not contribute to reduced global cognitive performance in treated hypertensive subjects. Nevertheless, our results suggest that both systolic BP and heart rate variability might be associated with modulation of frontal lobe cognitive domains, such as executive function and matrix reasoning.

  3. Influence of peer review on the reporting of primary outcome(s) and statistical analyses of randomised trials.

    Science.gov (United States)

    Hopewell, Sally; Witt, Claudia M; Linde, Klaus; Icke, Katja; Adedire, Olubusola; Kirtley, Shona; Altman, Douglas G

    2018-01-11

    Selective reporting of outcomes in clinical trials is a serious problem. We aimed to investigate the influence of the peer review process within biomedical journals on reporting of primary outcome(s) and statistical analyses within reports of randomised trials. Each month, PubMed (May 2014 to April 2015) was searched to identify primary reports of randomised trials published in six high-impact general and 12 high-impact specialty journals. The corresponding author of each trial was invited to complete an online survey asking authors about changes made to their manuscript as part of the peer review process. Our main outcomes were to assess: (1) the nature and extent of changes as part of the peer review process, in relation to reporting of the primary outcome(s) and/or primary statistical analysis; (2) how often authors followed these requests; and (3) whether this was related to specific journal or trial characteristics. Of 893 corresponding authors who were invited to take part in the online survey 258 (29%) responded. The majority of trials were multicentre (n = 191; 74%); median sample size 325 (IQR 138 to 1010). The primary outcome was clearly defined in 92% (n = 238), of which the direction of treatment effect was statistically significant in 49%. The majority responded (1-10 Likert scale) they were satisfied with the overall handling (mean 8.6, SD 1.5) and quality of peer review (mean 8.5, SD 1.5) of their manuscript. Only 3% (n = 8) said that the editor or peer reviewers had asked them to change or clarify the trial's primary outcome. However, 27% (n = 69) reported they were asked to change or clarify the statistical analysis of the primary outcome; most had fulfilled the request, the main motivation being to improve the statistical methods (n = 38; 55%) or avoid rejection (n = 30; 44%). Overall, there was little association between authors being asked to make this change and the type of journal, intervention, significance of the

  4. Consumer Loyalty and Loyalty Programs: a topographic examination of the scientific literature using bibliometrics, spatial statistics and network analyses

    Directory of Open Access Journals (Sweden)

    Viviane Moura Rocha

    2015-04-01

    Full Text Available This paper presents a topographic analysis of the fields of consumer loyalty and loyalty programs, vastly studied in the last decades and still relevant in the marketing literature. After the identification of 250 scientific papers that were published in the last ten years in indexed journals, a subset of 76 were chosen and their 3223 references were extracted. The journals in which these papers were published, their key words, abstracts, authors, institutions of origin and citation patterns were identified and analyzed using bibliometrics, spatial statistics techniques and network analyses. The results allow the identification of the central components of the field, as well as its main authors, journals, institutions and countries that intermediate the diffusion of knowledge, which contributes to the understanding of the constitution of the field by researchers and students.

  5. A new efficient statistical test for detecting variability in the gene expression data.

    Science.gov (United States)

    Mathur, Sunil; Dolo, Samuel

    2008-08-01

    DNA microarray technology allows researchers to monitor the expressions of thousands of genes under different conditions. The detection of differential gene expression under two different conditions is very important in microarray studies. Microarray experiments are multi-step procedures and each step is a potential source of variance. This makes the measurement of variability difficult because approach based on gene-by-gene estimation of variance will have few degrees of freedom. It is highly possible that the assumption of equal variance for all the expression levels may not hold. Also, the assumption of normality of gene expressions may not hold. Thus it is essential to have a statistical procedure which is not based on the normality assumption and also it can detect genes with differential variance efficiently. The detection of differential gene expression variance will allow us to identify experimental variables that affect different biological processes and accuracy of DNA microarray measurements.In this article, a new nonparametric test for scale is developed based on the arctangent of the ratio of two expression levels. Most of the tests available in literature require the assumption of normal distribution, which makes them inapplicable in many situations, and it is also hard to verify the suitability of the normal distribution assumption for the given data set. The proposed test does not require the assumption of the distribution for the underlying population and hence makes it more practical and widely applicable. The asymptotic relative efficiency is calculated under different distributions, which show that the proposed test is very powerful when the assumption of normality breaks down. Monte Carlo simulation studies are performed to compare the power of the proposed test with some of the existing procedures. It is found that the proposed test is more powerful than commonly used tests under almost all the distributions considered in the study. A

  6. Methods for Clustering Variables and the Use of them in Statistical Packages

    Czech Academy of Sciences Publication Activity Database

    Řezanková, H.; Húsek, Dušan

    2002-01-01

    Roč. 10, - (2002), s. 153-160 ISSN 1210-809X. [Applications of Mathematics and Statistics in Economy. Zadov, 13.09.2001-14.09.2001] R&D Projects: GA ČR GA201/01/1192 Institutional research plan: AV0Z1030915 Keywords : factor analysis * cluster analysis * multidimensional * statistical packages Subject RIV: BB - Applied Statistics, Operational Research

  7. A guide to statistical analysis in microbial ecology: a community-focused, living review of multivariate data analyses.

    Science.gov (United States)

    Buttigieg, Pier Luigi; Ramette, Alban

    2014-12-01

    The application of multivariate statistical analyses has become a consistent feature in microbial ecology. However, many microbial ecologists are still in the process of developing a deep understanding of these methods and appreciating their limitations. As a consequence, staying abreast of progress and debate in this arena poses an additional challenge to many microbial ecologists. To address these issues, we present the GUide to STatistical Analysis in Microbial Ecology (GUSTA ME): a dynamic, web-based resource providing accessible descriptions of numerous multivariate techniques relevant to microbial ecologists. A combination of interactive elements allows users to discover and navigate between methods relevant to their needs and examine how they have been used by others in the field. We have designed GUSTA ME to become a community-led and -curated service, which we hope will provide a common reference and forum to discuss and disseminate analytical techniques relevant to the microbial ecology community. © 2014 The Authors. FEMS Microbiology Ecology published by John Wiley & Sons Ltd on behalf of Federation of European Microbiological Societies.

  8. Assessing Regional Scale Variability in Extreme Value Statistics Under Altered Climate Scenarios

    Energy Technology Data Exchange (ETDEWEB)

    Brunsell, Nathaniel [Univ. of Kansas, Lawrence, KS (United States); Mechem, David [Univ. of Kansas, Lawrence, KS (United States); Ma, Chunsheng [Wichita State Univ., KS (United States)

    2015-02-20

    Recent studies have suggested that low-frequency modes of climate variability can significantly influence regional climate. The climatology associated with extreme events has been shown to be particularly sensitive. This has profound implications for droughts, heat waves, and food production. We propose to examine regional climate simulations conducted over the continental United States by applying a recently developed technique which combines wavelet multi–resolution analysis with information theory metrics. This research is motivated by two fundamental questions concerning the spatial and temporal structure of extreme events. These questions are 1) what temporal scales of the extreme value distributions are most sensitive to alteration by low-frequency climate forcings and 2) what is the nature of the spatial structure of variation in these timescales? The primary objective is to assess to what extent information theory metrics can be useful in characterizing the nature of extreme weather phenomena. Specifically, we hypothesize that (1) changes in the nature of extreme events will impact the temporal probability density functions and that information theory metrics will be sensitive these changes and (2) via a wavelet multi–resolution analysis, we will be able to characterize the relative contribution of different timescales on the stochastic nature of extreme events. In order to address these hypotheses, we propose a unique combination of an established regional climate modeling approach and advanced statistical techniques to assess the effects of low-frequency modes on climate extremes over North America. The behavior of climate extremes in RCM simulations for the 20th century will be compared with statistics calculated from the United States Historical Climatology Network (USHCN) and simulations from the North American Regional Climate Change Assessment Program (NARCCAP). This effort will serve to establish the baseline behavior of climate extremes, the

  9. Heart rate variability analysed by Poincaré plot in patients with metabolic syndrome

    Czech Academy of Sciences Publication Activity Database

    Kubíčková, A.; Kozumplík, J.; Nováková, Z.; Plachý, M.; Jurák, Pavel; Lipoldová, J.

    2016-01-01

    Roč. 49, č. 1 (2016), s. 23-28 ISSN 0022-0736 R&D Projects: GA ČR GAP102/12/2034 Institutional support: RVO:68081731 Keywords : heart rate variability * metabolic syndrome * Poincaré plot * tilt table test * controlled breathing Subject RIV: JA - Electronics ; Optoelectronics, Electrical Engineering Impact factor: 1.514, year: 2016

  10. Fatigue Crack Propagation Under Variable Amplitude Loading Analyses Based on Plastic Energy Approach

    Directory of Open Access Journals (Sweden)

    Sofiane Maachou

    2014-04-01

    Full Text Available Plasticity effects at the crack tip had been recognized as “motor” of crack propagation, the growth of cracks is related to the existence of a crack tip plastic zone, whose formation and intensification is accompanied by energy dissipation. In the actual state of knowledge fatigue crack propagation is modeled using crack closure concept. The fatigue crack growth behavior under constant amplitude and variable amplitude loading of the aluminum alloy 2024 T351 are analyzed using in terms energy parameters. In the case of VAL (variable amplitude loading tests, the evolution of the hysteretic energy dissipated per block is shown similar with that observed under constant amplitude loading. A linear relationship between the crack growth rate and the hysteretic energy dissipated per block is obtained at high growth rates. For lower growth rates values, the relationship between crack growth rate and hysteretic energy dissipated per block can represented by a power law. In this paper, an analysis of fatigue crack propagation under variable amplitude loading based on energetic approach is proposed.

  11. Statistical methodology for discrete fracture model - including fracture size, orientation uncertainty together with intensity uncertainty and variability

    Energy Technology Data Exchange (ETDEWEB)

    Darcel, C. (Itasca Consultants SAS (France)); Davy, P.; Le Goc, R.; Dreuzy, J.R. de; Bour, O. (Geosciences Rennes, UMR 6118 CNRS, Univ. def Rennes, Rennes (France))

    2009-11-15

    Investigations led for several years at Laxemar and Forsmark reveal the large heterogeneity of geological formations and associated fracturing. This project aims at reinforcing the statistical DFN modeling framework adapted to a site scale. This leads therefore to develop quantitative methods of characterization adapted to the nature of fracturing and data availability. We start with the hypothesis that the maximum likelihood DFN model is a power-law model with a density term depending on orientations. This is supported both by literature and specifically here by former analyses of the SKB data. This assumption is nevertheless thoroughly tested by analyzing the fracture trace and lineament maps. Fracture traces range roughly between 0.5 m and 10 m - i e the usual extension of the sample outcrops. Between the raw data and final data used to compute the fracture size distribution from which the size distribution model will arise, several steps are necessary, in order to correct data from finite-size, topographical and sampling effects. More precisely, a particular attention is paid to fracture segmentation status and fracture linkage consistent with the DFN model expected. The fracture scaling trend observed over both sites displays finally a shape parameter k{sub t} close to 1.2 with a density term (alpha{sub 2d}) between 1.4 and 1.8. Only two outcrops clearly display a different trend with k{sub t} close to 3 and a density term (alpha{sub 2d}) between 2 and 3.5. The fracture lineaments spread over the range between 100 meters and a few kilometers. When compared with fracture trace maps, these datasets are already interpreted and the linkage process developed previously has not to be done. Except for the subregional lineament map from Forsmark, lineaments display a clear power-law trend with a shape parameter k{sub t} equal to 3 and a density term between 2 and 4.5. The apparent variation in scaling exponent, from the outcrop scale (k{sub t} = 1.2) on one side, to

  12. On the Integrity of Online Testing for Introductory Statistics Courses: A Latent Variable Approach

    Directory of Open Access Journals (Sweden)

    Alan Fask

    2015-04-01

    Full Text Available There has been a remarkable growth in distance learning courses in higher education. Despite indications that distance learning courses are more vulnerable to cheating behavior than traditional courses, there has been little research studying whether online exams facilitate a relatively greater level of cheating. This article examines this issue by developing an approach using a latent variable to measure student cheating. This latent variable is linked to both known student mastery related variables and variables unrelated to student mastery. Grade scores from a proctored final exam and an unproctored final exam are used to test for increased cheating behavior in the unproctored exam

  13. Complexity analyses show two distinct types of nonlinear dynamics in short heart period variability recordings

    Science.gov (United States)

    Porta, Alberto; Bari, Vlasta; Marchi, Andrea; De Maria, Beatrice; Cysarz, Dirk; Van Leeuwen, Peter; Takahashi, Anielle C. M.; Catai, Aparecida M.; Gnecchi-Ruscone, Tomaso

    2015-01-01

    Two diverse complexity metrics quantifying time irreversibility and local prediction, in connection with a surrogate data approach, were utilized to detect nonlinear dynamics in short heart period (HP) variability series recorded in fetuses, as a function of the gestational period, and in healthy humans, as a function of the magnitude of the orthostatic challenge. The metrics indicated the presence of two distinct types of nonlinear HP dynamics characterized by diverse ranges of time scales. These findings stress the need to render more specific the analysis of nonlinear components of HP dynamics by accounting for different temporal scales. PMID:25806002

  14. Understanding Short-Term Nonmigrating Tidal Variability in the Ionospheric Dynamo Region from SABER Using Information Theory and Bayesian Statistics

    Science.gov (United States)

    Kumari, K.; Oberheide, J.

    2017-12-01

    Nonmigrating tidal diagnostics of SABER temperature observations in the ionospheric dynamo region reveal a large amount of variability on time-scales of a few days to weeks. In this paper, we discuss the physical reasons for the observed short-term tidal variability using a novel approach based on Information theory and Bayesian statistics. We diagnose short-term tidal variability as a function of season, QBO, ENSO, and solar cycle and other drivers using time dependent probability density functions, Shannon entropy and Kullback-Leibler divergence. The statistical significance of the approach and its predictive capability is exemplified using SABER tidal diagnostics with emphasis on the responses to the QBO and solar cycle. Implications for F-region plasma density will be discussed.

  15. Computational modeling and statistical analyses on individual contact rate and exposure to disease in complex and confined transportation hubs

    Science.gov (United States)

    Wang, W. L.; Tsui, K. L.; Lo, S. M.; Liu, S. B.

    2018-01-01

    Crowded transportation hubs such as metro stations are thought as ideal places for the development and spread of epidemics. However, for the special features of complex spatial layout, confined environment with a large number of highly mobile individuals, it is difficult to quantify human contacts in such environments, wherein disease spreading dynamics were less explored in the previous studies. Due to the heterogeneity and dynamic nature of human interactions, increasing studies proved the importance of contact distance and length of contact in transmission probabilities. In this study, we show how detailed information on contact and exposure patterns can be obtained by statistical analyses on microscopic crowd simulation data. To be specific, a pedestrian simulation model-CityFlow was employed to reproduce individuals' movements in a metro station based on site survey data, values and distributions of individual contact rate and exposure in different simulation cases were obtained and analyzed. It is interesting that Weibull distribution fitted the histogram values of individual-based exposure in each case very well. Moreover, we found both individual contact rate and exposure had linear relationship with the average crowd densities of the environments. The results obtained in this paper can provide reference to epidemic study in complex and confined transportation hubs and refine the existing disease spreading models.

  16. Research Pearls: The Significance of Statistics and Perils of Pooling. Part 3: Pearls and Pitfalls of Meta-analyses and Systematic Reviews.

    Science.gov (United States)

    Harris, Joshua D; Brand, Jefferson C; Cote, Mark P; Dhawan, Aman

    2017-08-01

    Within the health care environment, there has been a recent and appropriate trend towards emphasizing the value of care provision. Reduced cost and higher quality improve the value of care. Quality is a challenging, heterogeneous, variably defined concept. At the core of quality is the patient's outcome, quantified by a vast assortment of subjective and objective outcome measures. There has been a recent evolution towards evidence-based medicine in health care, clearly elucidating the role of high-quality evidence across groups of patients and studies. Synthetic studies, such as systematic reviews and meta-analyses, are at the top of the evidence-based medicine hierarchy. Thus, these investigations may be the best potential source of guiding diagnostic, therapeutic, prognostic, and economic medical decision making. Systematic reviews critically appraise and synthesize the best available evidence to provide a conclusion statement (a "take-home point") in response to a specific answerable clinical question. A meta-analysis uses statistical methods to quantitatively combine data from single studies. Meta-analyses should be performed with high methodological quality homogenous studies (Level I or II) or evidence randomized studies, to minimize confounding variable bias. When it is known that the literature is inadequate or a recent systematic review has already been performed with a demonstration of insufficient data, then a new systematic review does not add anything meaningful to the literature. PROSPERO registration and PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines assist authors in the design and conduct of systematic reviews and should always be used. Complete transparency of the conduct of the review permits reproducibility and improves fidelity of the conclusions. Pooling of data from overly dissimilar investigations should be avoided. This particularly applies to Level IV evidence, that is, noncomparative investigations

  17. Statistics for Ratios of Rayleigh, Rician, Nakagami-m, and Weibull Distributed Random Variables

    Directory of Open Access Journals (Sweden)

    Dragana Č. Pavlović

    2013-01-01

    Full Text Available The distributions of ratios of random variables are of interest in many areas of the sciences. In this brief paper, we present the joint probability density function (PDF and PDF of maximum of ratios μ1=R1/r1 and μ2=R2/r2 for the cases where R1, R2, r1, and r2 are Rayleigh, Rician, Nakagami-m, and Weibull distributed random variables. Random variables R1 and R2, as well as random variables r1 and r2, are correlated. Ascertaining on the suitability of the Weibull distribution to describe fading in both indoor and outdoor environments, special attention is dedicated to the case of Weibull random variables. For this case, analytical expressions for the joint PDF, PDF of maximum, PDF of minimum, and product moments of arbitrary number of ratios μi=Ri/ri, i=1,…,L are obtained. Random variables in numerator, Ri, as well as random variables in denominator, ri, are exponentially correlated. To the best of the authors' knowledge, analytical expressions for the PDF of minimum and product moments of {μi}i=1L are novel in the open technical literature. The proposed mathematical analysis is complemented by various numerical results. An application of presented theoretical results is illustrated with respect to performance assessment of wireless systems.

  18. An MGF-based unified framework to determine the joint statistics of partial sums of ordered random variables

    KAUST Repository

    Nam, Sungsik

    2010-11-01

    Order statistics find applications in various areas of communications and signal processing. In this paper, we introduce an unified analytical framework to determine the joint statistics of partial sums of ordered random variables (RVs). With the proposed approach, we can systematically derive the joint statistics of any partial sums of ordered statistics, in terms of the moment generating function (MGF) and the probability density function (PDF). Our MGF-based approach applies not only when all the K ordered RVs are involved but also when only the Ks(Ks < K) best RVs are considered. In addition, we present the closed-form expressions for the exponential RV special case. These results apply to the performance analysis of various wireless communication systems over fading channels. © 2006 IEEE.

  19. A Meta-Meta-Analysis: Empirical Review of Statistical Power, Type I Error Rates, Effect Sizes, and Model Selection of Meta-Analyses Published in Psychology

    Science.gov (United States)

    Cafri, Guy; Kromrey, Jeffrey D.; Brannick, Michael T.

    2010-01-01

    This article uses meta-analyses published in "Psychological Bulletin" from 1995 to 2005 to describe meta-analyses in psychology, including examination of statistical power, Type I errors resulting from multiple comparisons, and model choice. Retrospective power estimates indicated that univariate categorical and continuous moderators, individual…

  20. Heart rate variability analysed by Poincaré plot in patients with metabolic syndrome.

    Science.gov (United States)

    Kubičková, Alena; Kozumplík, Jiří; Nováková, Zuzana; Plachý, Martin; Jurák, Pavel; Lipoldová, Jolana

    2016-01-01

    The SD1 and SD2 indexes (standard deviations in two orthogonal directions of the Poincaré plot) carry similar information to the spectral density power of the high and low frequency bands but have the advantage of easier calculation and lesser stationarity dependence. ECG signals from metabolic syndrome (MetS) and control group patients during tilt table test under controlled breathing (20 breaths/minute) were obtained. SD1, SD2, SDRR (standard deviation of RR intervals) and RMSSD (root mean square of successive differences of RR intervals) were evaluated for 31 control group and 33 MetS subjects. Statistically significant lower values were observed in MetS patients in supine position (SD1: p=0.03, SD2: p=0.002, SDRR: p=0.006, RMSSD: p=0.01) and during tilt (SD2: p=0.004, SDRR: p=0.007). SD1 and SD2 combining the advantages of time and frequency domain methods, distinguish successfully between MetS and control subjects. Copyright © 2016 Elsevier Inc. All rights reserved.

  1. Tree Ring Analyses Unlock a Century of Hydroclimatic Variability Across the Himalayas

    Science.gov (United States)

    Brunello, C. F.; Andermann, C.; Helle, G.; Comiti, F.; Tonon, G.; Hovius, N.

    2017-12-01

    Climate change has altered precipitation patterns and impacted the spatio-temporal distribution and availability of water in high mountain environments. For example, intensification of the Indian Summer Monsoon (ISM) increases the potential for moisture laden air to breach the Himalayan orographic barrier and penetrate into the arid, elevated southern Tibetan Plateau, with geomorphological and hydrological consequences. Such trends should be considered against a solid background, but a consistent record of centennial monsoon dynamics in the trans-Himalayan region has never been developed. Instrumental data are sparse and only cover a limited time period as well as remotely sensed information. Meanwhile, models have major systematic bias and substantial uncertainty in reproducing ISM interannual variability. In this context, hydro-climatic proxies, such as oxygen stable isotope ratios in cellulose of tree rings, are a valuable source of data, especially because isotope mass spectroscopy can unlock yearly resolved information by tracing the isotopic signature (18O) stored within each growth ring. Here we present three centennial records of monsoon dynamics, along a latitudinal transect, spanning a pronounced precipitation gradient across the Himalayan orogen. Three sites were selected along the Kali Gandaki valley in the central Himalayas (Nepal), this valley connects the wet, monsoon dominated Gangetic plain with the arid Tibetan Plateau. Our transect covers the sensitive northern end of the precipitation gradient, located in the upper part of the catchment. Our results show that inter-annual variation of monsoon strength can be reconstructed by tree ring δ18O. The inferred monsoon dynamics are compared against independent constraints on precipitation, snow cover and river discharge. Different water sources contribute disproportionally at the three sites, reflecting spatial and temporal shifts of the westerlies and the Indian summer monsoon. These two dominant

  2. The spatial variable glacier mass loss over the southeast Tibet Plateau and the climate cause analyses

    Science.gov (United States)

    Ke, L.; Ding, X.; Song, C.; Sheng, Y.

    2016-12-01

    Temperate glaciers can be highly sensitive to global climate change due to relatively humid and warm local climate. Numerous temperate glaciers are distributed in the southeastern Tibet Plateau (SETP) and their changes are still poorly represented. Based on a latest glacier inventory and ICESat altimetry measurements, we examine the spatial heterogeneity of glacier change in the SETP (including the central and eastern Nyainqêntanglha ranges) and further analyze its relation with climate change by using station-based and gridded meteorological data. Our results show that SETP glaciers experienced drastic surface lowering at about -0.84±0.26 m a-1 on average over 2003-2008. Debris-covered ice thinned at an average rate of -1.13±0.32 m a-1, in comparison with -0.92±0.17 m a-1 over the debris-free ice areas. The thinning rate is the strongest in the southeastern sub-region (up to -1.24 m a-1 ) and moderate ( -0.45 m a-1 ) in the central and northwestern parts, which is in general agreement with the pattern of surface mass changes based on the GRACE gravimetry observation. Long-term climate data at weather stations show that, in comparison with the period of 1992-2002, mean temperature increased by 0.46 °C - 0.59 °C in the recent decade (2003-2013); while the change of summer precipitation exhibited remarkably spatial variability, following a southeast-northwest contrasting pattern (decreasing by over 10% in the southeast, to stable level in the central region, and increment up to 10% in the northwest). This spatially variable precipitation change is consistent with results from CN05 grid data and ERA re-analysis data, and agrees well with the spatial pattern of glacier surface elevation changes. The results suggest that overall negative glacier mass balances in SETP are governed by temperature rising, while the different precipitation change could contribute to inconsistent glacier thinning rates. The spatial pattern of precipitation decrease and mass loss might

  3. Energy saving analyses on the reconstruction project in district heating system with distributed variable speed pumps

    International Nuclear Information System (INIS)

    Sheng, Xianjie; Lin, Duanmu

    2016-01-01

    Highlights: • The mathematical model of economic frictional factor based on DVFSP DHS is established. • Influence factors of economic frictional factor are analyzed. • Energy saving in a DVFSP district heating system is presented and analyzed. - Abstract: Optimization of the district heating (DH) piping network is of vital importance to the economics of the whole DH system. The application of distributed variable frequency speed pump (DVFSP) in the district heating network has been considered as a technology improvement that has a potential in saving energy compared to the conventional central circulating pump (CCCP) district heating system (DHS). Economic frictional factor is a common design parameter used in DH pipe network design. In this paper, the mathematical model of economic frictional factor based on DVFSP DHS is established, and influence factors are analyzed, providing a reference for engineering designs for the system. According to the analysis results, it is studied that the energy efficiency in the DH system with the DVFSP is compared with the one in the DH system with conventional central circulating pump (CCCP) using a case based on a district heating network in Dalian, China. The results of the study on the case show that the average electrical energy saved is 49.41% of the one saved by the DH system with conventional central circulating pump in the primary network.

  4. Van ‘t Hoff global analyses of variable temperature isothermal titration calorimetry data

    International Nuclear Information System (INIS)

    Freiburger, Lee A.; Auclair, Karine; Mittermaier, Anthony K.

    2012-01-01

    Highlights: ▶ We developed a global fitting strategy for ITC data collected at multiple temperatures. ▶ This method does not require prior knowledge of the binding mechanism. ▶ Monte Carlo simulations show that the approach improves the accuracy of extracted thermodynamic parameters. ▶ The method is used to study coupled folding/binding in aminoglycoside 6′-N-acetyltransferase-Ii. - Abstract: Isothermal titration calorimetry (ITC) can provide detailed information on the thermodynamics of biomolecular interactions in the form of equilibrium constants, K A , and enthalpy changes, ΔH A . A powerful application of this technique involves analyzing the temperature dependences of ITC-derived K A and ΔH A values to gain insight into thermodynamic linkage between binding and additional equilibria, such as protein folding. We recently developed a general method for global analysis of variable temperature ITC data that significantly improves the accuracy of extracted thermodynamic parameters and requires no prior knowledge of the coupled equilibria. Here we report detailed validation of this method using Monte Carlo simulations and an application to study coupled folding and binding in an aminoglycoside acetyltransferase enzyme.

  5. Evaluation of multivariate statistical analyses for monitoring and prediction of processes in an seawater reverse osmosis desalination plant

    International Nuclear Information System (INIS)

    Kolluri, Srinivas Sahan; Esfahani, Iman Janghorban; Garikiparthy, Prithvi Sai Nadh; Yoo, Chang Kyoo

    2015-01-01

    Our aim was to analyze, monitor, and predict the outcomes of processes in a full-scale seawater reverse osmosis (SWRO) desalination plant using multivariate statistical techniques. Multivariate analysis of variance (MANOVA) was used to investigate the performance and efficiencies of two SWRO processes, namely, pore controllable fiber filterreverse osmosis (PCF-SWRO) and sand filtration-ultra filtration-reverse osmosis (SF-UF-SWRO). Principal component analysis (PCA) was applied to monitor the two SWRO processes. PCA monitoring revealed that the SF-UF-SWRO process could be analyzed reliably with a low number of outliers and disturbances. Partial least squares (PLS) analysis was then conducted to predict which of the seven input parameters of feed flow rate, PCF/SF-UF filtrate flow rate, temperature of feed water, turbidity feed, pH, reverse osmosis (RO)flow rate, and pressure had a significant effect on the outcome variables of permeate flow rate and concentration. Root mean squared errors (RMSEs) of the PLS models for permeate flow rates were 31.5 and 28.6 for the PCF-SWRO process and SF-UF-SWRO process, respectively, while RMSEs of permeate concentrations were 350.44 and 289.4, respectively. These results indicate that the SF-UF-SWRO process can be modeled more accurately than the PCF-SWRO process, because the RMSE values of permeate flowrate and concentration obtained using a PLS regression model of the SF-UF-SWRO process were lower than those obtained for the PCF-SWRO process.

  6. Evaluation of multivariate statistical analyses for monitoring and prediction of processes in an seawater reverse osmosis desalination plant

    Energy Technology Data Exchange (ETDEWEB)

    Kolluri, Srinivas Sahan; Esfahani, Iman Janghorban; Garikiparthy, Prithvi Sai Nadh; Yoo, Chang Kyoo [Kyung Hee University, Yongin (Korea, Republic of)

    2015-08-15

    Our aim was to analyze, monitor, and predict the outcomes of processes in a full-scale seawater reverse osmosis (SWRO) desalination plant using multivariate statistical techniques. Multivariate analysis of variance (MANOVA) was used to investigate the performance and efficiencies of two SWRO processes, namely, pore controllable fiber filterreverse osmosis (PCF-SWRO) and sand filtration-ultra filtration-reverse osmosis (SF-UF-SWRO). Principal component analysis (PCA) was applied to monitor the two SWRO processes. PCA monitoring revealed that the SF-UF-SWRO process could be analyzed reliably with a low number of outliers and disturbances. Partial least squares (PLS) analysis was then conducted to predict which of the seven input parameters of feed flow rate, PCF/SF-UF filtrate flow rate, temperature of feed water, turbidity feed, pH, reverse osmosis (RO)flow rate, and pressure had a significant effect on the outcome variables of permeate flow rate and concentration. Root mean squared errors (RMSEs) of the PLS models for permeate flow rates were 31.5 and 28.6 for the PCF-SWRO process and SF-UF-SWRO process, respectively, while RMSEs of permeate concentrations were 350.44 and 289.4, respectively. These results indicate that the SF-UF-SWRO process can be modeled more accurately than the PCF-SWRO process, because the RMSE values of permeate flowrate and concentration obtained using a PLS regression model of the SF-UF-SWRO process were lower than those obtained for the PCF-SWRO process.

  7. Analyses of heart rate variability in young soccer players: the effects of sport activity.

    Science.gov (United States)

    Bricout, Véronique-Aurélie; Dechenaud, Simon; Favre-Juvin, Anne

    2010-04-19

    The use of heart rate variability (HRV) in the management of sport training is a practice which tends to spread, especially in order to prevent the occurrence of states of fatigue. To estimate the HRV parameters obtained using a heart rate recording, according to different loads of sporting activities, and to make the possible link with the appearance of fatigue. Eight young football players, aged 14.6 years+/-2 months, playing at league level in Rhône-Alpes, training for 10 to 20 h per week, were followed over a period of 5 months, allowing to obtain 54 recordings of HRV in three different conditions: (i) after rest (ii) after a day with training and (iii) after a day with a competitive match. Under the effect of a competitive match, the HRV temporal indicators (heart rate, RR interval, and pNN50) were significantly altered compared to the rest day. The analysis of the sympathovagal balance rose significantly as a result of the competitive constraint (0.72+/-0.17 vs. 0.90+/-0.20; pHRV is an objective and non-invasive monitoring of management of the training of young sportsmen. HRV analysis allowed to highlight any neurovegetative adjustments according to the physical loads. Thus, under the effect of an increase of physical and psychological constraints that a football match represents, the LF/HF ratio rises significantly; reflecting increased sympathetic stimulation, which beyond certain limits could be relevant to prevent the emergence of a state of fatigue. 2009 Elsevier B.V. All rights reserved.

  8. Interest of analyses of heart rate variability in the prevention of fatigue states in senior runners.

    Science.gov (United States)

    Leti, Thomas; Bricout, Véronique A

    2013-01-01

    The use of heart rate variability (HRV) in the management of sport training is a practice which tends to spread, especially in order to prevent the occurrence of fatigue states. To estimate the HRV parameters obtained using a heart rate recording, according to different exercise impacts, and to make the link with the appearance of subjective fatigue. Ten senior runners, aged 51±5 years, were each monitored over a period of 12 weeks in different conditions: (i) after a resting period, (ii) after a day with training, (iii) after a day of competition and (iv) after a rest day. They also completed three questionnaires, to assess fatigue (SFMS), profile of mood states (POMS) and quality of sleep. The HRV indices (heart rate, LF (n.u.), HF (n.u.) and LF/HF) were significantly altered with the competitive impact, shifting toward a sympathetic predominance. After rest and recovery nights, the LF (n.u.) increased significantly with the competitive impact (62.1±15.2 and 66.9±11.6 vs. 76.0±10.7; p<0.05 respectively) whereas the HF (n.u.) decreased significantly (37.9±15.2 and 33.1±11.6 vs. 24.0±10.7; p<0.05 respectively). Positive correlations were found between fatigue and frequency domain indices and between fatigue and training impact. Autonomic nervous system modulation-fatigue relationships were significant, suggesting the potential use of HRV in follow-up and control of training. Furthermore, the addition of questionnaires constitutes complementary tools that allow to achieve a greater relevance and accuracy of the athletes' fitness and results. Copyright © 2012 Elsevier B.V. All rights reserved.

  9. Statistical Analysis for Multisite Trials Using Instrumental Variables with Random Coefficients

    Science.gov (United States)

    Raudenbush, Stephen W.; Reardon, Sean F.; Nomi, Takako

    2012-01-01

    Multisite trials can clarify the average impact of a new program and the heterogeneity of impacts across sites. Unfortunately, in many applications, compliance with treatment assignment is imperfect. For these applications, we propose an instrumental variable (IV) model with person-specific and site-specific random coefficients. Site-specific IV…

  10. Sea Surface Height Variability and Eddy Statistical Properties in the Red Sea

    KAUST Repository

    Zhan, Peng

    2013-01-01

    Satellite sea surface height (SSH) data over 1992-2012 are analyzed to study the spatial and temporal variability of sea level in the Red Sea. Empirical orthogonal functions (EOF) analysis suggests the remarkable seasonality of SSH in the Red Sea

  11. Statistically extracted fundamental watershed variables for estimating the loads of total nitrogen in small streams

    Science.gov (United States)

    Kronholm, Scott C.; Capel, Paul D.; Terziotti, Silvia

    2016-01-01

    Accurate estimation of total nitrogen loads is essential for evaluating conditions in the aquatic environment. Extrapolation of estimates beyond measured streams will greatly expand our understanding of total nitrogen loading to streams. Recursive partitioning and random forest regression were used to assess 85 geospatial, environmental, and watershed variables across 636 small (monitoring may be beneficial.

  12. Identification of novel risk factors for community-acquired Clostridium difficile infection using spatial statistics and geographic information system analyses.

    Directory of Open Access Journals (Sweden)

    Deverick J Anderson

    Full Text Available The rate of community-acquired Clostridium difficile infection (CA-CDI is increasing. While receipt of antibiotics remains an important risk factor for CDI, studies related to acquisition of C. difficile outside of hospitals are lacking. As a result, risk factors for exposure to C. difficile in community settings have been inadequately studied.To identify novel environmental risk factors for CA-CDI.We performed a population-based retrospective cohort study of patients with CA-CDI from 1/1/2007 through 12/31/2014 in a 10-county area in central North Carolina. 360 Census Tracts in these 10 counties were used as the demographic Geographic Information System (GIS base-map. Longitude and latitude (X, Y coordinates were generated from patient home addresses and overlaid to Census Tracts polygons using ArcGIS; ArcView was used to assess "hot-spots" or clusters of CA-CDI. We then constructed a mixed hierarchical model to identify environmental variables independently associated with increased rates of CA-CDI.A total of 1,895 unique patients met our criteria for CA-CDI. The mean patient age was 54.5 years; 62% were female and 70% were Caucasian. 402 (21% patient addresses were located in "hot spots" or clusters of CA-CDI (p<0.001. "Hot spot" census tracts were scattered throughout the 10 counties. After adjusting for clustering and population density, age ≥ 60 years (p = 0.03, race (<0.001, proximity to a livestock farm (0.01, proximity to farming raw materials services (0.02, and proximity to a nursing home (0.04 were independently associated with increased rates of CA-CDI.Our study is the first to use spatial statistics and mixed models to identify important environmental risk factors for acquisition of C. difficile and adds to the growing evidence that farm practices may put patients at risk for important drug-resistant infections.

  13. The effects of clinical and statistical heterogeneity on the predictive values of results from meta-analyses

    NARCIS (Netherlands)

    Melsen, W G; Rovers, M M; Bonten, M J M; Bootsma, M C J|info:eu-repo/dai/nl/304830305

    Variance between studies in a meta-analysis will exist. This heterogeneity may be of clinical, methodological or statistical origin. The last of these is quantified by the I(2) -statistic. We investigated, using simulated studies, the accuracy of I(2) in the assessment of heterogeneity and the

  14. Statistically Enhanced Model of In Situ Oil Sands Extraction Operations: An Evaluation of Variability in Greenhouse Gas Emissions.

    Science.gov (United States)

    Orellana, Andrea; Laurenzi, Ian J; MacLean, Heather L; Bergerson, Joule A

    2018-02-06

    Greenhouse gas (GHG) emissions associated with extraction of bitumen from oil sands can vary from project to project and over time. However, the nature and magnitude of this variability have yet to be incorporated into life cycle studies. We present a statistically enhanced life cycle based model (GHOST-SE) for assessing variability of GHG emissions associated with the extraction of bitumen using in situ techniques in Alberta, Canada. It employs publicly available, company-reported operating data, facilitating assessment of inter- and intraproject variability as well as the time evolution of GHG emissions from commercial in situ oil sands projects. We estimate the median GHG emissions associated with bitumen production via cyclic steam stimulation (CSS) to be 77 kg CO 2 eq/bbl bitumen (80% CI: 61-109 kg CO 2 eq/bbl), and via steam assisted gravity drainage (SAGD) to be 68 kg CO 2 eq/bbl bitumen (80% CI: 49-102 kg CO 2 eq/bbl). We also show that the median emissions intensity of Alberta's CSS and SAGD projects have been relatively stable from 2000 to 2013, despite greater than 6-fold growth in production. Variability between projects is the single largest source of variability (driven in part by reservoir characteristics) but intraproject variability (e.g., startups, interruptions), is also important and must be considered in order to inform research or policy priorities.

  15. ICUD-0147 Extreme event statistics of urban pluvial floods – Return period assessment and rainfall variability impacts

    DEFF Research Database (Denmark)

    Tuyls, Damian Murla; Nielsen, Rasmus; Thorndahl, Søren Liedtke

    2017-01-01

    A return period assessment of urban flood has been performed and its adhered impact of rainfall variability studied over a urban drainage catchment area in Aalborg, Denmark. Recorded rainfall from 7 rain gauges has been used, located in a range of 7.5Km and for a period varying form 18-37 years....... Return period of rainfall and flood at catchment and local scale has been estimated, its derived ambiguities analysed and the variability of rain gauge based rainfall investigated regarding to flood estimation results. Results show a clear contrast between rainfall and flood return period estimates...

  16. Developing a spatial-statistical model and map of historical malaria prevalence in Botswana using a staged variable selection procedure

    Directory of Open Access Journals (Sweden)

    Mabaso Musawenkosi LH

    2007-09-01

    Full Text Available Abstract Background Several malaria risk maps have been developed in recent years, many from the prevalence of infection data collated by the MARA (Mapping Malaria Risk in Africa project, and using various environmental data sets as predictors. Variable selection is a major obstacle due to analytical problems caused by over-fitting, confounding and non-independence in the data. Testing and comparing every combination of explanatory variables in a Bayesian spatial framework remains unfeasible for most researchers. The aim of this study was to develop a malaria risk map using a systematic and practicable variable selection process for spatial analysis and mapping of historical malaria risk in Botswana. Results Of 50 potential explanatory variables from eight environmental data themes, 42 were significantly associated with malaria prevalence in univariate logistic regression and were ranked by the Akaike Information Criterion. Those correlated with higher-ranking relatives of the same environmental theme, were temporarily excluded. The remaining 14 candidates were ranked by selection frequency after running automated step-wise selection procedures on 1000 bootstrap samples drawn from the data. A non-spatial multiple-variable model was developed through step-wise inclusion in order of selection frequency. Previously excluded variables were then re-evaluated for inclusion, using further step-wise bootstrap procedures, resulting in the exclusion of another variable. Finally a Bayesian geo-statistical model using Markov Chain Monte Carlo simulation was fitted to the data, resulting in a final model of three predictor variables, namely summer rainfall, mean annual temperature and altitude. Each was independently and significantly associated with malaria prevalence after allowing for spatial correlation. This model was used to predict malaria prevalence at unobserved locations, producing a smooth risk map for the whole country. Conclusion We have

  17. Radiocaesium in grazing sheep. A statistical analysis of variability, survey methodology and long term behaviour

    Energy Technology Data Exchange (ETDEWEB)

    Mehli, H

    1996-05-01

    Since 1987 sheep grazing in the areas of Norway that received Chernobyl-fallout have been monitored before slaughter. These monitoring data formed the basis for development of a model describing the long term behaviour of radiocesium in unimproved pasture showing that in years with good mushroom abundance 70-80% of the radiocesium concentration in sheep is due to fungi consumption. A study of sampling strategy and variability of radiocesium concentration within flocks was also performed. 55 refs., 31 figs., 15 tabs.

  18. Radiocaesium in grazing sheep. A statistical analysis of variability, survey methodology and long term behaviour

    International Nuclear Information System (INIS)

    Mehli, H.

    1996-05-01

    Since 1987 sheep grazing in the areas of Norway that received Chernobyl-fallout have been monitored before slaughter. These monitoring data formed the basis for development of a model describing the long term behaviour of radiocesium in unimproved pasture showing that in years with good mushroom abundance 70-80% of the radiocesium concentration in sheep is due to fungi consumption. A study of sampling strategy and variability of radiocesium concentration within flocks was also performed. 55 refs., 31 figs., 15 tabs

  19. A New Statistical Approach to the Optical Spectral Variability in Blazars

    Directory of Open Access Journals (Sweden)

    Jose A. Acosta-Pulido

    2016-12-01

    Full Text Available We present a spectral variability study of a sample of about 25 bright blazars, based on optical spectroscopy. Observations cover the period from the end of 2008 to mid 2015, with an approximately monthly cadence. Emission lines have been identified and measured in the spectra, which permits us to classify the sources into BL Lac-type or FSRQs, according to the commonly used EW limit. We have obtained synthetic photometry and produced colour-magnitude diagrams which show different trends associated with the object classes: generally, BL Lacs tend to become bluer when brighter and FSRQs become redder when brighter, although several objects exhibit both trends, depending on brightness. We have also applied a pattern recognition algorithm to obtain the minimum number of physical components which can explain the variability of the optical spectrum. We have used NMF (Non-Negative Matrix Factorization instead of PCA (Principal Component Analysis to avoid un-realistic negative components. For most targets we found that 2 or 3 meta-components are enough to explain the observed spectral variability.

  20. Multi-Site and Multi-Variables Statistical Downscaling Technique in the Monsoon Dominated Region of Pakistan

    Science.gov (United States)

    Khan, Firdos; Pilz, Jürgen

    2016-04-01

    South Asia is under the severe impacts of changing climate and global warming. The last two decades showed that climate change or global warming is happening and the first decade of 21st century is considered as the warmest decade over Pakistan ever in history where temperature reached 53 0C in 2010. Consequently, the spatio-temporal distribution and intensity of precipitation is badly effected and causes floods, cyclones and hurricanes in the region which further have impacts on agriculture, water, health etc. To cope with the situation, it is important to conduct impact assessment studies and take adaptation and mitigation remedies. For impact assessment studies, we need climate variables at higher resolution. Downscaling techniques are used to produce climate variables at higher resolution; these techniques are broadly divided into two types, statistical downscaling and dynamical downscaling. The target location of this study is the monsoon dominated region of Pakistan. One reason for choosing this area is because the contribution of monsoon rains in this area is more than 80 % of the total rainfall. This study evaluates a statistical downscaling technique which can be then used for downscaling climatic variables. Two statistical techniques i.e. quantile regression and copula modeling are combined in order to produce realistic results for climate variables in the area under-study. To reduce the dimension of input data and deal with multicollinearity problems, empirical orthogonal functions will be used. Advantages of this new method are: (1) it is more robust to outliers as compared to ordinary least squares estimates and other estimation methods based on central tendency and dispersion measures; (2) it preserves the dependence among variables and among sites and (3) it can be used to combine different types of distributions. This is important in our case because we are dealing with climatic variables having different distributions over different meteorological

  1. Observer variability in the assessment of type and dysplasia of colorectal adenomas, analyzed using kappa statistics

    DEFF Research Database (Denmark)

    Jensen, P; Krogsgaard, M R; Christiansen, J

    1995-01-01

    . The kappa values for Observer A vs. B and Observer C vs. B were 0.3480 and 0.3770, respectively (both type and dysplasia). Values for type were better than for dysplasia, but agreement was only fair to moderate. CONCLUSION: The interobserver agreement was moderate to almost perfect, but the intraobserver...... agreement was only fair to moderate. A simpler classification system or a centralization of assessments would probably increase kappa values....... of adenomas were assessed twice by three experienced pathologists, with an interval of two months. Results were analyzed using kappa statistics. RESULTS: For agreement between first and second assessment (both type and grade of dysplasia), kappa values for the three specialists were 0.5345, 0.9022, and 0...

  2. The effect of a graphical interpretation of a statistic trend indicator (Trigg's Tracking Variable) on the detection of simulated changes.

    Science.gov (United States)

    Kennedy, R R; Merry, A F

    2011-09-01

    Anaesthesia involves processing large amounts of information over time. One task of the anaesthetist is to detect substantive changes in physiological variables promptly and reliably. It has been previously demonstrated that a graphical trend display of historical data leads to more rapid detection of such changes. We examined the effect of a graphical indication of the magnitude of Trigg's Tracking Variable, a simple statistically based trend detection algorithm, on the accuracy and latency of the detection of changes in a micro-simulation. Ten anaesthetists each viewed 20 simulations with four variables displayed as the current value with a simple graphical trend display. Values for these variables were generated by a computer model, and updated every second; after a period of stability a change occurred to a new random value at least 10 units from baseline. In 50% of the simulations an indication of the rate of change was given by a five level graphical representation of the value of Trigg's Tracking Variable. Participants were asked to indicate when they thought a change was occurring. Changes were detected 10.9% faster with the trend indicator present (mean 13.1 [SD 3.1] cycles vs 14.6 [SD 3.4] cycles, 95% confidence interval 0.4 to 2.5 cycles, P = 0.013. There was no difference in accuracy of detection (median with trend detection 97% [interquartile range 95 to 100%], without trend detection 100% [98 to 100%]), P = 0.8. We conclude that simple statistical trend detection may speed detection of changes during routine anaesthesia, even when a graphical trend display is present.

  3. Cancer Statistics Animator

    Science.gov (United States)

    This tool allows users to animate cancer trends over time by cancer site and cause of death, race, and sex. Provides access to incidence, mortality, and survival. Select the type of statistic, variables, format, and then extract the statistics in a delimited format for further analyses.

  4. The moderator-mediator variable distinction in social psychological research: conceptual, strategic, and statistical considerations.

    Science.gov (United States)

    Baron, R M; Kenny, D A

    1986-12-01

    In this article, we attempt to distinguish between the properties of moderator and mediator variables at a number of levels. First, we seek to make theorists and researchers aware of the importance of not using the terms moderator and mediator interchangeably by carefully elaborating, both conceptually and strategically, the many ways in which moderators and mediators differ. We then go beyond this largely pedagogical function and delineate the conceptual and strategic implications of making use of such distinctions with regard to a wide range of phenomena, including control and stress, attitudes, and personality traits. We also provide a specific compendium of analytic procedures appropriate for making the most effective use of the moderator and mediator distinction, both separately and in terms of a broader causal system that includes both moderators and mediators.

  5. Japanese standard method for safety evaluation using best estimate code based on uncertainty and scaling analyses with statistical approach

    International Nuclear Information System (INIS)

    Mizokami, Shinya; Hotta, Akitoshi; Kudo, Yoshiro; Yonehara, Tadashi; Watada, Masayuki; Sakaba, Hiroshi

    2009-01-01

    Current licensing practice in Japan consists of using conservative boundary and initial conditions(BIC), assumptions and analytical codes. The safety analyses for licensing purpose are inherently deterministic. Therefore, conservative BIC and assumptions, such as single failure, must be employed for the analyses. However, using conservative analytical codes are not considered essential. The standard committee of Atomic Energy Society of Japan(AESJ) has drawn up the standard for using best estimate codes for safety analyses in 2008 after three-years of discussions reflecting domestic and international recent findings. (author)

  6. To what extent does variability of historical rainfall series influence extreme event statistics of sewer system surcharge and overflows?

    Science.gov (United States)

    Schaarup-Jensen, K; Rasmussen, M R; Thorndahl, S

    2009-01-01

    In urban drainage modelling long-term extreme statistics has become an important basis for decision-making e.g. in connection with renovation projects. Therefore it is of great importance to minimize the uncertainties with regards to long-term prediction of maximum water levels and combined sewer overflow (CSO) in drainage systems. These uncertainties originate from large uncertainties regarding rainfall inputs, parameters, and assessment of return periods. This paper investigates how the choice of rainfall time series influences the extreme events statistics of max water levels in manholes and CSO volumes. Traditionally, long-term rainfall series, from a local rain gauge, are unavailable. In the present case study, however, long and local rain series are available. 2 rainfall gauges have recorded events for approximately 9 years at 2 locations within the catchment. Beside these 2 gauges another 7 gauges are located at a distance of max 20 kilometers from the catchment. All gauges are included in the Danish national rain gauge system which was launched in 1976. The paper describes to what extent the extreme events statistics based on these 9 series diverge from each other and how this diversity can be handled, e.g. by introducing an "averaging procedure" based on the variability within the set of statistics. All simulations are performed by means of the MOUSE LTS model.

  7. Statistical analysis of morphometric indicators and physical readiness variability of students

    Directory of Open Access Journals (Sweden)

    R.A. Gainullin

    2017-10-01

    Full Text Available Aim: To evaluate the interaction of morphometric characteristics with the reactions of the cardiorespiratory system and the indices of physical training during the process of physical exercise training at the university. Material: The students of the first course (n = 91, aged 17-18 took part in the survey. The students were divided into 6 groups. All students were engaged in physical training. All the studied indicators were conditionally divided into two groups. The first group of studies included indicators of physical fitness. The second group was formed by morphofunctional indices. Results: The indicators of the physical preparedness of students demonstrate a wide range and heterogeneity. This should be taken into account when staffing training groups. When using the technique of development of local regional muscular endurance, the values of orthostatic test and the Skibinski index show significant variability. Also high and significant correlation interactions are shown by indicators: manual dynamometry; strength endurance; the values of the Skibinski index. Also, in the orthotropic test, the same effect was observed: age, body length, heart rate. A similar analysis of morphofunctional indices shows significant correlation links: the Skibinski index and orthotropic tests; age and the Skibinski index; weight and body length. Conclusions: from the point of view of physical fitness, groups of sports training (the second group and hypertensive groups (group 5 proved to be the most stable. A group of volunteers turned out to be the most stable relative to the morphofunctional indicators.

  8. Adjusting the Adjusted X[superscript 2]/df Ratio Statistic for Dichotomous Item Response Theory Analyses: Does the Model Fit?

    Science.gov (United States)

    Tay, Louis; Drasgow, Fritz

    2012-01-01

    Two Monte Carlo simulation studies investigated the effectiveness of the mean adjusted X[superscript 2]/df statistic proposed by Drasgow and colleagues and, because of problems with the method, a new approach for assessing the goodness of fit of an item response theory model was developed. It has been previously recommended that mean adjusted…

  9. Descriptive statistics and spatial distributions of geochemical variables associated with manganese oxide-rich phases in the northern Pacific

    Science.gov (United States)

    Botbol, Joseph Moses; Evenden, Gerald Ian

    1989-01-01

    Tables, graphs, and maps are used to portray the frequency characteristics and spatial distribution of manganese oxide-rich phase geochemical data, to characterize the northern Pacific in terms of publicly available nodule geochemical data, and to develop data portrayal methods that will facilitate data analysis. Source data are a subset of the Scripps Institute of Oceanography's Sediment Data Bank. The study area is bounded by 0° N., 40° N., 120° E., and 100° W. and is arbitrarily subdivided into 14-20°x20° geographic subregions. Frequency distributions of trace metals characterized in the original raw data are graphed as ogives, and salient parameters are tabulated. All variables are transformed to enrichment values relative to median concentration within their host subregions. Scatter plots of all pairs of original variables and their enrichment transforms are provided as an aid to the interpretation of correlations between variables. Gridded spatial distributions of all variables are portrayed as gray-scale maps. The use of tables and graphs to portray frequency statistics and gray-scale maps to portray spatial distributions is an effective way to prepare for and facilitate multivariate data analysis.

  10. Statistical methods for the analysis of left-censored variables [Statistische Analysemethoden für linkszensierte Variablen und Beobachtungen mit Werten unterhalb einer Bestimmungs- oder Nachweisgrenze

    Directory of Open Access Journals (Sweden)

    Pesch, Beate

    2013-03-01

    Full Text Available [english] In some applications statisticians are confronted with values which are reported to be below a limit of detection or quantitation. These left-censored variables are a challenge in the statistical analysis. In a simulation study, we compare different methods to deal with this type of data in statistical applications. These include measures of location, dispersion, association, and statistical modeling. Our simulation study showed that the multiple imputation approach and the Tobit regression lead to unbiased estimates, whereas the naïve methods including simple substitution of non-detects lead to unreliable estimates. We illustrate the application of the multiple imputation approach and the Tobit regression with an example from occupational epidemiology. [german] In der statistischen Praxis treten immer wieder Variablen mit Werten unterhalb einer Bestimmungs- oder Nachweisgrenze auf. Diese sind linkszensiert und stellen daher eine Herausforderung für die statistische Analyse dar. Im Rahmen einer Simulationsstudie vergleichen wir Schätzmethoden zur Berechnung von Lage- und Streuungmaßen, Korrelationen und Regressionsparametern bei diesen Variablen. Unsere Ergebnisse zeigen, dass die multiple Imputationsmethode und die Tobit Regression zu unverzerrten Schätzungen führen. Naive Methoden, einschließlich der einfachen Substitution von zensierten Beobachtungen, ergeben hingegen unzuverlässige Schätzungen. Wir illustrieren die Anwendung der multiplen Imputationsmethode und der Tobit Regression anhand eines Beispiels aus der Epidemiologie der Arbeitswelt.

  11. First study of correlation between oleic acid content and SAD gene polymorphism in olive oil samples through statistical and bayesian modeling analyses.

    Science.gov (United States)

    Ben Ayed, Rayda; Ennouri, Karim; Ercişli, Sezai; Ben Hlima, Hajer; Hanana, Mohsen; Smaoui, Slim; Rebai, Ahmed; Moreau, Fabienne

    2018-04-10

    Virgin olive oil is appreciated for its particular aroma and taste and is recognized worldwide for its nutritional value and health benefits. The olive oil contains a vast range of healthy compounds such as monounsaturated free fatty acids, especially, oleic acid. The SAD.1 polymorphism localized in the Stearoyl-acyl carrier protein desaturase gene (SAD) was genotyped and showed that it is associated with the oleic acid composition of olive oil samples. However, the effect of polymorphisms in fatty acid-related genes on olive oil monounsaturated and saturated fatty acids distribution in the Tunisian olive oil varieties is not understood. Seventeen Tunisian olive-tree varieties were selected for fatty acid content analysis by gas chromatography. The association of SAD.1 genotypes with the fatty acids composition was studied by statistical and Bayesian modeling analyses. Fatty acid content analysis showed interestingly that some Tunisian virgin olive oil varieties could be classified as a functional food and nutraceuticals due to their particular richness in oleic acid. In fact, the TT-SAD.1 genotype was found to be associated with a higher proportion of mono-unsaturated fatty acids (MUFA), mainly oleic acid (C18:1) (r = - 0.79, p SAD.1 association with the oleic acid composition of olive oil was identified among the studied varieties. This correlation fluctuated between studied varieties, which might elucidate variability in lipidic composition among them and therefore reflecting genetic diversity through differences in gene expression and biochemical pathways. SAD locus would represent an excellent marker for identifying interesting amongst virgin olive oil lipidic composition.

  12. ANALYSES OF GENETIC VARIABILITY IN LENTINULA EDODES THROUGH MYCELIA RESPONSES TO DIFFERENT ABIOTIC CONDITIONS AND RAPD MOLECULAR MARKERS

    Directory of Open Access Journals (Sweden)

    Maki Cristina Sayuri

    2001-01-01

    Full Text Available The growth of thirty-four Lentinula edodes strains submitted to different mycelial cultivation conditions (pH and temperature was evaluated and strain variability was assessed by RAPD molecular markers. The growth at three pH values (5, 6 and 7 and four different temperatures (16, 25, 28 and 37ºC was measured using the in vitro mycelial development rate and water retention as parameters. Mycelial cultivation was successful at all pH tested, while the ideal temperature for mycelial cultivation ranged between 25 and 28ºC. The water content was lower in strains grown at 37ºC. Among 20 OPA primers (Operon Technologies, Inc. used for the RAPD analyses, seventeen presented good polymorphism (OPA01 to OPA05, OPA07 to OPA14, OPA17 to OPA20. The clustering based on similarity coefficients allowed the separation of strain in two groups with different geographic origins.

  13. Selecting statistical models and variable combinations for optimal classification using otolith microchemistry.

    Science.gov (United States)

    Mercier, Lény; Darnaude, Audrey M; Bruguier, Olivier; Vasconcelos, Rita P; Cabral, Henrique N; Costa, Maria J; Lara, Monica; Jones, David L; Mouillot, David

    2011-06-01

    Reliable assessment of fish origin is of critical importance for exploited species, since nursery areas must be identified and protected to maintain recruitment to the adult stock. During the last two decades, otolith chemical signatures (or "fingerprints") have been increasingly used as tools to discriminate between coastal habitats. However, correct assessment of fish origin from otolith fingerprints depends on various environmental and methodological parameters, including the choice of the statistical method used to assign fish to unknown origin. Among the available methods of classification, Linear Discriminant Analysis (LDA) is the most frequently used, although it assumes data are multivariate normal with homogeneous within-group dispersions, conditions that are not always met by otolith chemical data, even after transformation. Other less constrained classification methods are available, but there is a current lack of comparative analysis in applications to otolith microchemistry. Here, we assessed stock identification accuracy for four classification methods (LDA, Quadratic Discriminant Analysis [QDA], Random Forests [RF], and Artificial Neural Networks [ANN]), through the use of three distinct data sets. In each case, all possible combinations of chemical elements were examined to identify the elements to be used for optimal accuracy in fish assignment to their actual origin. Our study shows that accuracy differs according to the model and the number of elements considered. Best combinations did not include all the elements measured, and it was not possible to define an ad hoc multielement combination for accurate site discrimination. Among all the models tested, RF and ANN performed best, especially for complex data sets (e.g., with numerous fish species and/or chemical elements involved). However, for these data, RF was less time-consuming and more interpretable than ANN, and far more efficient and less demanding in terms of assumptions than LDA or QDA

  14. Dynamics of heart rate variability analysed through nonlinear and linear dynamics is already impaired in young type 1 diabetic subjects.

    Science.gov (United States)

    Souza, Naiara M; Giacon, Thais R; Pacagnelli, Francis L; Barbosa, Marianne P C R; Valenti, Vitor E; Vanderlei, Luiz C M

    2016-10-01

    Autonomic diabetic neuropathy is one of the most common complications of type 1 diabetes mellitus, and studies using heart rate variability to investigate these individuals have shown inconclusive results regarding autonomic nervous system activation. Aims To investigate the dynamics of heart rate in young subjects with type 1 diabetes mellitus through nonlinear and linear methods of heart rate variability. We evaluated 20 subjects with type 1 diabetes mellitus and 23 healthy control subjects. We obtained the following nonlinear indices from the recurrence plot: recurrence rate (REC), determinism (DET), and Shanon entropy (ES), and we analysed indices in the frequency (LF and HF in ms2 and normalised units - nu - and LF/HF ratio) and time domains (SDNN and RMSSD), through analysis of 1000 R-R intervals, captured by a heart rate monitor. There were reduced values (p<0.05) for individuals with type 1 diabetes mellitus compared with healthy subjects in the following indices: DET, REC, ES, RMSSD, SDNN, LF (ms2), and HF (ms2). In relation to the recurrence plot, subjects with type 1 diabetes mellitus demonstrated lower recurrence and greater variation in their plot, inter-group and intra-group, respectively. Young subjects with type 1 diabetes mellitus have autonomic nervous system behaviour that tends to randomness compared with healthy young subjects. Moreover, this behaviour is related to reduced sympathetic and parasympathetic activity of the autonomic nervous system.

  15. Guided waves based SHM systems for composites structural elements: statistical analyses finalized at probability of detection definition and assessment

    Science.gov (United States)

    Monaco, E.; Memmolo, V.; Ricci, F.; Boffa, N. D.; Maio, L.

    2015-03-01

    Maintenance approaches based on sensorised structures and Structural Health Monitoring systems could represent one of the most promising innovations in the fields of aerostructures since many years, mostly when composites materials (fibers reinforced resins) are considered. Layered materials still suffer today of drastic reductions of maximum allowable stress values during the design phase as well as of costly and recurrent inspections during the life cycle phase that don't permit of completely exploit their structural and economic potentialities in today aircrafts. Those penalizing measures are necessary mainly to consider the presence of undetected hidden flaws within the layered sequence (delaminations) or in bonded areas (partial disbonding); in order to relax design and maintenance constraints a system based on sensors permanently installed on the structure to detect and locate eventual flaws can be considered (SHM system) once its effectiveness and reliability will be statistically demonstrated via a rigorous Probability Of Detection function definition and evaluation. This paper presents an experimental approach with a statistical procedure for the evaluation of detection threshold of a guided waves based SHM system oriented to delaminations detection on a typical wing composite layered panel. The experimental tests are mostly oriented to characterize the statistical distribution of measurements and damage metrics as well as to characterize the system detection capability using this approach. Numerically it is not possible to substitute part of the experimental tests aimed at POD where the noise in the system response is crucial. Results of experiments are presented in the paper and analyzed.

  16. New Statistical Model for Variability of Aerosol Optical Thickness: Theory and Application to MODIS Data over Ocean

    Science.gov (United States)

    Alexandrov, Mikhail Dmitrievic; Geogdzhayev, Igor V.; Tsigaridis, Konstantinos; Marshak, Alexander; Levy, Robert; Cairns, Brian

    2016-01-01

    A novel model for the variability in aerosol optical thickness (AOT) is presented. This model is based on the consideration of AOT fields as realizations of a stochastic process, that is the exponent of an underlying Gaussian process with a specific autocorrelation function. In this approach AOT fields have lognormal PDFs and structure functions having the correct asymptotic behavior at large scales. The latter is an advantage compared with fractal (scale-invariant) approaches. The simple analytical form of the structure function in the proposed model facilitates its use for the parameterization of AOT statistics derived from remote sensing data. The new approach is illustrated using a month-long global MODIS AOT dataset (over ocean) with 10 km resolution. It was used to compute AOT statistics for sample cells forming a grid with 5deg spacing. The observed shapes of the structure functions indicated that in a large number of cases the AOT variability is split into two regimes that exhibit different patterns of behavior: small-scale stationary processes and trends reflecting variations at larger scales. The small-scale patterns are suggested to be generated by local aerosols within the marine boundary layer, while the large-scale trends are indicative of elevated aerosols transported from remote continental sources. This assumption is evaluated by comparison of the geographical distributions of these patterns derived from MODIS data with those obtained from the GISS GCM. This study shows considerable potential to enhance comparisons between remote sensing datasets and climate models beyond regional mean AOTs.

  17. Data base for the analysis of compositional characteristics of coal seams and macerals. Final report - Part 10. Variability in the inorganic content of United States' coals: a multivariate statistical study

    Energy Technology Data Exchange (ETDEWEB)

    Glick, D.C.; Davis, A.

    1984-07-01

    The multivariate statistical techniques of correlation coefficients, factor analysis, and cluster analysis, implemented by computer programs, can be used to process a large data set and produce a summary of relationships between variables and between samples. These techniques were used to find relationships for data on the inorganic constituents of US coals. Three hundred thirty-five whole-seam channel samples from six US coal provinces were analyzed for inorganic variables. After consideration of the attributes of data expressed on ash basis and whole-coal basis, it was decided to perform complete statistical analyses on both data sets. Thirty variables expressed on whole-coal basis and twenty-six variables expressed on ash basis were used. For each inorganic variable, a frequency distribution histogram and a set of summary statistics was produced. These were subdivided to reveal the manner in which concentrations of inorganic constituents vary between coal provinces and between coal regions. Data collected on 124 samples from three stratigraphic groups (Pottsville, Monongahela, Allegheny) in the Appalachian region were studied using analysis of variance to determine degree of variability between stratigraphic levels. Most variables showed differences in mean values between the three groups. 193 references, 71 figures, 54 tables.

  18. A Systematic Review of Statistical Methods Used to Test for Reliability of Medical Instruments Measuring Continuous Variables

    Directory of Open Access Journals (Sweden)

    Rafdzah Zaki

    2013-06-01

    Full Text Available   Objective(s: Reliability measures precision or the extent to which test results can be replicated. This is the first ever systematic review to identify statistical methods used to measure reliability of equipment measuring continuous variables. This studyalso aims to highlight the inappropriate statistical method used in the reliability analysis and its implication in the medical practice.   Materials and Methods: In 2010, five electronic databases were searched between 2007 and 2009 to look for reliability studies. A total of 5,795 titles were initially identified. Only 282 titles were potentially related, and finally 42 fitted the inclusion criteria. Results: The Intra-class Correlation Coefficient (ICC is the most popular method with 25 (60% studies having used this method followed by the comparing means (8 or 19%. Out of 25 studies using the ICC, only 7 (28% reported the confidence intervals and types of ICC used. Most studies (71% also tested the agreement of instruments. Conclusion: This study finds that the Intra-class Correlation Coefficient is the most popular method used to assess the reliability of medical instruments measuring continuous outcomes. There are also inappropriate applications and interpretations of statistical methods in some studies. It is important for medical researchers to be aware of this issue, and be able to correctly perform analysis in reliability studies.

  19. Analyses of statistical transformations of row data describing free proline concentration in sugar beet exposed to drought

    Directory of Open Access Journals (Sweden)

    Putnik-Delić Marina I.

    2010-01-01

    Full Text Available Eleven sugar beet genotypes were tested for their capacity to tolerate drought. Plants were grown in semi-controlled conditions, in the greenhouse, and watered daily. After 90 days, water deficit was imposed by the cessation of watering, while the control plants continued to be watered up to 80% of FWC. Five days later concentration of free proline in leaves was determined. Analysis was done in three replications. Statistical analysis was performed using STATISTICA 9.0, Minitab 15, and R2.11.1. Differences between genotypes were statistically processed by Duncan test. Because of nonormality of the data distribution and heterogeneity of variances in different groups, two types of transformations of row data were applied. For this type of data more appropriate in eliminating nonormality was Johnson transformation, as opposed to Box-Cox. Based on the both transformations it may be concluded that in all genotypes except for 10, concentration of free proline differs significantly between treatment (drought and the control.

  20. Using synthetic data to evaluate multiple regression and principal component analyses for statistical modeling of daily building energy consumption

    Energy Technology Data Exchange (ETDEWEB)

    Reddy, T.A. (Energy Systems Lab., Texas A and M Univ., College Station, TX (United States)); Claridge, D.E. (Energy Systems Lab., Texas A and M Univ., College Station, TX (United States))

    1994-01-01

    Multiple regression modeling of monitored building energy use data is often faulted as a reliable means of predicting energy use on the grounds that multicollinearity between the regressor variables can lead both to improper interpretation of the relative importance of the various physical regressor parameters and to a model with unstable regressor coefficients. Principal component analysis (PCA) has the potential to overcome such drawbacks. While a few case studies have already attempted to apply this technique to building energy data, the objectives of this study were to make a broader evaluation of PCA and multiple regression analysis (MRA) and to establish guidelines under which one approach is preferable to the other. Four geographic locations in the US with different climatic conditions were selected and synthetic data sequence representative of daily energy use in large institutional buildings were generated in each location using a linear model with outdoor temperature, outdoor specific humidity and solar radiation as the three regression variables. MRA and PCA approaches were then applied to these data sets and their relative performances were compared. Conditions under which PCA seems to perform better than MRA were identified and preliminary recommendations on the use of either modeling approach formulated. (orig.)

  1. Point processes statistics of stable isotopes: analysing water uptake patterns in a mixed stand of Aleppo pine and Holm oak

    Directory of Open Access Journals (Sweden)

    Carles Comas

    2015-04-01

    Full Text Available Aim of study: Understanding inter- and intra-specific competition for water is crucial in drought-prone environments. However, little is known about the spatial interdependencies for water uptake among individuals in mixed stands. The aim of this work was to compare water uptake patterns during a drought episode in two common Mediterranean tree species, Quercus ilex L. and Pinus halepensis Mill., using the isotope composition of xylem water (δ18O, δ2H as hydrological marker. Area of study: The study was performed in a mixed stand, sampling a total of 33 oaks and 78 pines (plot area= 888 m2. We tested the hypothesis that both species uptake water differentially along the soil profile, thus showing different levels of tree-to-tree interdependency, depending on whether neighbouring trees belong to one species or the other. Material and Methods: We used pair-correlation functions to study intra-specific point-tree configurations and the bivariate pair correlation function to analyse the inter-specific spatial configuration. Moreover, the isotopic composition of xylem water was analysed as a mark point pattern. Main results: Values for Q. ilex (δ18O = –5.3 ± 0.2‰, δ2H = –54.3 ± 0.7‰ were significantly lower than for P. halepensis (δ18O = –1.2 ± 0.2‰, δ2H = –25.1 ± 0.8‰, pointing to a greater contribution of deeper soil layers for water uptake by Q. ilex. Research highlights: Point-process analyses revealed spatial intra-specific dependencies among neighbouring pines, showing neither oak-oak nor oak-pine interactions. This supports niche segregation for water uptake between the two species.

  2. Statistical Metadata Analysis of the Variability of Latency, Device Transfer Time, and Coordinate Position from Smartphone-Recorded Infrasound Data

    Science.gov (United States)

    Garces, E. L.; Garces, M. A.; Christe, A.

    2017-12-01

    The RedVox infrasound recorder app uses microphones and barometers in smartphones to record infrasound, low-frequency sound below the threshold of human hearing. We study a device's metadata, which includes position, latency time, the differences between the device's internal times and the server times, and the machine time, searching for patterns and possible errors or discontinuities in these scaled parameters. We highlight metadata variability through scaled multivariate displays (histograms, distribution curves, scatter plots), all created and organized through software development in Python. This project is helpful in ascertaining variability and honing the accuracy of smartphones, aiding the emergence of portable devices as viable geophysical data collection instruments. It can also improve the app and cloud service by increasing efficiency and accuracy, allowing to better document and foresee drastic natural movements like tsunamis, earthquakes, volcanic eruptions, storms, rocket launches, and meteor impacts; recorded data can later be used for studies and analysis by a variety of professions. We expect our final results to produce insight on how to counteract problematic issues in data mining and improve accuracy in smartphone data-collection. By eliminating lurking variables and minimizing the effect of confounding variables, we hope to discover efficient processes to reduce superfluous precision, unnecessary errors, and data artifacts. These methods should conceivably be transferable to other areas of software development, data analytics, and statistics-based experiments, contributing a precedent of smartphone metadata studies from geophysical rather than societal data. The results should facilitate the rise of civilian-accessible, hand-held, data-gathering mobile sensor networks and yield more straightforward data mining techniques.

  3. Quantitative X-ray Map Analyser (Q-XRMA): A new GIS-based statistical approach to Mineral Image Analysis

    Science.gov (United States)

    Ortolano, Gaetano; Visalli, Roberto; Godard, Gaston; Cirrincione, Rosolino

    2018-06-01

    We present a new ArcGIS®-based tool developed in the Python programming language for calibrating EDS/WDS X-ray element maps, with the aim of acquiring quantitative information of petrological interest. The calibration procedure is based on a multiple linear regression technique that takes into account interdependence among elements and is constrained by the stoichiometry of minerals. The procedure requires an appropriate number of spot analyses for use as internal standards and provides several test indexes for a rapid check of calibration accuracy. The code is based on an earlier image-processing tool designed primarily for classifying minerals in X-ray element maps; the original Python code has now been enhanced to yield calibrated maps of mineral end-members or the chemical parameters of each classified mineral. The semi-automated procedure can be used to extract a dataset that is automatically stored within queryable tables. As a case study, the software was applied to an amphibolite-facies garnet-bearing micaschist. The calibrated images obtained for both anhydrous (i.e., garnet and plagioclase) and hydrous (i.e., biotite) phases show a good fit with corresponding electron microprobe analyses. This new GIS-based tool package can thus find useful application in petrology and materials science research. Moreover, the huge quantity of data extracted opens new opportunities for the development of a thin-section microchemical database that, using a GIS platform, can be linked with other major global geoscience databases.

  4. Exploring the physical controls of regional patterns of flow duration curves – Part 1: Insights from statistical analyses

    Directory of Open Access Journals (Sweden)

    S. Ye

    2012-11-01

    Full Text Available The flow duration curve (FDC is a classical method used to graphically represent the relationship between the frequency and magnitude of streamflow. In this sense it represents a compact signature of temporal runoff variability that can also be used to diagnose catchment rainfall-runoff responses, including similarity and differences between catchments. This paper is aimed at extracting regional patterns of the FDCs from observed daily flow data and elucidating the physical controls underlying these patterns, as a way to aid towards their regionalization and predictions in ungauged basins. The FDCs of total runoff (TFDC using multi-decadal streamflow records for 197 catchments across the continental United States are separated into the FDCs of two runoff components, i.e., fast flow (FFDC and slow flow (SFDC. In order to compactly display these regional patterns, the 3-parameter mixed gamma distribution is employed to characterize the shapes of the normalized FDCs (i.e., TFDC, FFDC and SFDC over the entire data record. This is repeated to also characterize the between-year variability of "annual" FDCs for 8 representative catchments chosen across a climate gradient. Results show that the mixed gamma distribution can adequately capture the shapes of the FDCs and their variation between catchments and also between years. Comparison between the between-catchment and between-year variability of the FDCs revealed significant space-time symmetry. Possible relationships between the parameters of the fitted mixed gamma distribution and catchment climatic and physiographic characteristics are explored in order to decipher and point to the underlying physical controls. The baseflow index (a surrogate for the collective impact of geology, soils, topography and vegetation, as well as climate is found to be the dominant control on the shapes of the normalized TFDC and SFDC, whereas the product of maximum daily precipitation and the fraction of non-rainy days

  5. Influence of Immersion Conditions on The Tensile Strength of Recycled Kevlar®/Polyester/Low-Melting-Point Polyester Nonwoven Geotextiles through Applying Statistical Analyses

    Directory of Open Access Journals (Sweden)

    Jing-Chzi Hsieh

    2016-05-01

    Full Text Available The recycled Kevlar®/polyester/low-melting-point polyester (recycled Kevlar®/PET/LPET nonwoven geotextiles are immersed in neutral, strong acid, and strong alkali solutions, respectively, at different temperatures for four months. Their tensile strength is then tested according to various immersion periods at various temperatures, in order to determine their durability to chemicals. For the purpose of analyzing the possible factors that influence mechanical properties of geotextiles under diverse environmental conditions, the experimental results and statistical analyses are incorporated in this study. Therefore, influences of the content of recycled Kevlar® fibers, implementation of thermal treatment, and immersion periods on the tensile strength of recycled Kevlar®/PET/LPET nonwoven geotextiles are examined, after which their influential levels are statistically determined by performing multiple regression analyses. According to the results, the tensile strength of nonwoven geotextiles can be enhanced by adding recycled Kevlar® fibers and thermal treatment.

  6. El Niño-Southern Oscillation-based index insurance for floods: Statistical risk analyses and application to Peru

    Science.gov (United States)

    Khalil, Abedalrazq F.; Kwon, Hyun-Han; Lall, Upmanu; Miranda, Mario J.; Skees, Jerry

    2007-10-01

    Index insurance has recently been advocated as a useful risk transfer tool for disaster management situations where rapid fiscal relief is desirable and where estimating insured losses may be difficult, time consuming, or subject to manipulation and falsification. For climate-related hazards, a rainfall or temperature index may be proposed. However, rainfall may be highly spatially variable relative to the gauge network, and in many locations, data are inadequate to develop an index because of short time series and the spatial dispersion of stations. In such cases, it may be helpful to consider a climate proxy index as a regional rainfall index. This is particularly useful if a long record is available for the climate index through an independent source and it is well correlated with the regional rainfall hazard. Here El Niño-Southern Oscillation (ENSO) related climate indices are explored for use as a proxy to extreme rainfall in one of the districts of Peru, Piura. The ENSO index insurance product may be purchased by banks or microfinance institutions to aid agricultural damage relief in Peru. Crop losses in the region are highly correlated with floods but are difficult to assess directly. Beyond agriculture, many other sectors suffer as well. Basic infrastructure is destroyed during the most severe events. This disrupts trade for many microenterprises. The reliability and quality of the local rainfall data are variable. Averaging the financial risk across the region is desirable. Some issues with the implementation of the proxy ENSO index are identified and discussed. Specifically, we explore (1) the reliability of the index at different levels of probability of exceedance of maximum seasonal rainfall, (2) the effect of sampling uncertainties and the strength of the proxy's association to local outcome, (3) the potential for clustering of payoffs, (4) the potential that the index could be predicted with some lead time prior to the flood season, and (5) evidence

  7. Application of statistical experimental design to study the formulation variables influencing the coating process of lidocaine liposomes.

    Science.gov (United States)

    González-Rodríguez, M L; Barros, L B; Palma, J; González-Rodríguez, P L; Rabasco, A M

    2007-06-07

    In this paper, we have used statistical experimental design to investigate the effect of several factors in coating process of lidocaine hydrochloride (LID) liposomes by a biodegradable polymer (chitosan, CH). These variables were the concentration of CH coating solution, the dripping rate of this solution on the liposome colloidal dispersion, the stirring rate, the time since the liposome production to the liposome coating and finally the amount of drug entrapped into liposomes. The selected response variables were drug encapsulation efficiency (EE, %), coating efficiency (CE, %) and zeta potential. Liposomes were obtained by thin-layer evaporation method. They were subsequently coated with CH according the experimental plan provided by a fractional factorial (2(5-1)) screening matrix. We have used spectroscopic methods to determine the zeta potential values. The EE (%) assay was carried out in dialysis bags and the brilliant red probe was used to determine CE (%) due to its property of forming molecular complexes with CH. The graphic analysis of the effects allowed the identification of the main formulation and technological factors by the analysis of the selected responses and permitted the determination of the proper level of these factors for the response improvement. Moreover, fractional design allowed quantifying the interactions between the factors, which will consider in next experiments. The results obtained pointed out that LID amount was the predominant factor that increased the drug entrapment capacity (EE). The CE (%) response was mainly affected by the concentration of the CH solution and the stirring rate, although all the interactions between the main factors have statistical significance.

  8. Statistical and molecular analyses of evolutionary significance of red-green color vision and color blindness in vertebrates.

    Science.gov (United States)

    Yokoyama, Shozo; Takenaka, Naomi

    2005-04-01

    Red-green color vision is strongly suspected to enhance the survival of its possessors. Despite being red-green color blind, however, many species have successfully competed in nature, which brings into question the evolutionary advantage of achieving red-green color vision. Here, we propose a new method of identifying positive selection at individual amino acid sites with the premise that if positive Darwinian selection has driven the evolution of the protein under consideration, then it should be found mostly at the branches in the phylogenetic tree where its function had changed. The statistical and molecular methods have been applied to 29 visual pigments with the wavelengths of maximal absorption at approximately 510-540 nm (green- or middle wavelength-sensitive [MWS] pigments) and at approximately 560 nm (red- or long wavelength-sensitive [LWS] pigments), which are sampled from a diverse range of vertebrate species. The results show that the MWS pigments are positively selected through amino acid replacements S180A, Y277F, and T285A and that the LWS pigments have been subjected to strong evolutionary conservation. The fact that these positively selected M/LWS pigments are found not only in animals with red-green color vision but also in those with red-green color blindness strongly suggests that both red-green color vision and color blindness have undergone adaptive evolution independently in different species.

  9. Quantifying Trace Amounts of Aggregates in Biopharmaceuticals Using Analytical Ultracentrifugation Sedimentation Velocity: Bayesian Analyses and F Statistics.

    Science.gov (United States)

    Wafer, Lucas; Kloczewiak, Marek; Luo, Yin

    2016-07-01

    Analytical ultracentrifugation-sedimentation velocity (AUC-SV) is often used to quantify high molar mass species (HMMS) present in biopharmaceuticals. Although these species are often present in trace quantities, they have received significant attention due to their potential immunogenicity. Commonly, AUC-SV data is analyzed as a diffusion-corrected, sedimentation coefficient distribution, or c(s), using SEDFIT to numerically solve Lamm-type equations. SEDFIT also utilizes maximum entropy or Tikhonov-Phillips regularization to further allow the user to determine relevant sample information, including the number of species present, their sedimentation coefficients, and their relative abundance. However, this methodology has several, often unstated, limitations, which may impact the final analysis of protein therapeutics. These include regularization-specific effects, artificial "ripple peaks," and spurious shifts in the sedimentation coefficients. In this investigation, we experimentally verified that an explicit Bayesian approach, as implemented in SEDFIT, can largely correct for these effects. Clear guidelines on how to implement this technique and interpret the resulting data, especially for samples containing micro-heterogeneity (e.g., differential glycosylation), are also provided. In addition, we demonstrated how the Bayesian approach can be combined with F statistics to draw more accurate conclusions and rigorously exclude artifactual peaks. Numerous examples with an antibody and an antibody-drug conjugate were used to illustrate the strengths and drawbacks of each technique.

  10. Ultimate compression after impact load prediction in graphite/epoxy coupons using neural network and multivariate statistical analyses

    Science.gov (United States)

    Gregoire, Alexandre David

    2011-07-01

    The goal of this research was to accurately predict the ultimate compressive load of impact damaged graphite/epoxy coupons using a Kohonen self-organizing map (SOM) neural network and multivariate statistical regression analysis (MSRA). An optimized use of these data treatment tools allowed the generation of a simple, physically understandable equation that predicts the ultimate failure load of an impacted damaged coupon based uniquely on the acoustic emissions it emits at low proof loads. Acoustic emission (AE) data were collected using two 150 kHz resonant transducers which detected and recorded the AE activity given off during compression to failure of thirty-four impacted 24-ply bidirectional woven cloth laminate graphite/epoxy coupons. The AE quantification parameters duration, energy and amplitude for each AE hit were input to the Kohonen self-organizing map (SOM) neural network to accurately classify the material failure mechanisms present in the low proof load data. The number of failure mechanisms from the first 30% of the loading for twenty-four coupons were used to generate a linear prediction equation which yielded a worst case ultimate load prediction error of 16.17%, just outside of the +/-15% B-basis allowables, which was the goal for this research. Particular emphasis was placed upon the noise removal process which was largely responsible for the accuracy of the results.

  11. Statistical variability comparison in MODIS and AERONET derived aerosol optical depth over Indo-Gangetic Plains using time series modeling.

    Science.gov (United States)

    Soni, Kirti; Parmar, Kulwinder Singh; Kapoor, Sangeeta; Kumar, Nishant

    2016-05-15

    A lot of studies in the literature of Aerosol Optical Depth (AOD) done by using Moderate Resolution Imaging Spectroradiometer (MODIS) derived data, but the accuracy of satellite data in comparison to ground data derived from ARrosol Robotic NETwork (AERONET) has been always questionable. So to overcome from this situation, comparative study of a comprehensive ground based and satellite data for the period of 2001-2012 is modeled. The time series model is used for the accurate prediction of AOD and statistical variability is compared to assess the performance of the model in both cases. Root mean square error (RMSE), mean absolute percentage error (MAPE), stationary R-squared, R-squared, maximum absolute percentage error (MAPE), normalized Bayesian information criterion (NBIC) and Ljung-Box methods are used to check the applicability and validity of the developed ARIMA models revealing significant precision in the model performance. It was found that, it is possible to predict the AOD by statistical modeling using time series obtained from past data of MODIS and AERONET as input data. Moreover, the result shows that MODIS data can be formed from AERONET data by adding 0.251627 ± 0.133589 and vice-versa by subtracting. From the forecast available for AODs for the next four years (2013-2017) by using the developed ARIMA model, it is concluded that the forecasted ground AOD has increased trend. Copyright © 2016 Elsevier B.V. All rights reserved.

  12. Phenomenological and statistical analyses of turbulence in forced convection with temperature-dependent viscosity under non-Boussinesq condition.

    Science.gov (United States)

    Yahya, S M; Anwer, S F; Sanghi, S

    2013-10-01

    In this work, Thermal Large Eddy Simulation (TLES) is performed to study the behavior of weakly compressible Newtonian fluids with anisotropic temperature-dependent viscosity in forced convection turbulent flow. A systematic analysis of variable-viscosity effects, isolated from gravity, with relevance to industrial cooling/heating applications is being carried out. A LES of a planar channel flow with significant heat transfer at a low Mach number was performed to study effects of fluid property variation on the near-wall turbulence structure. In this flow configuration the top wall is maintained at a higher temperature (T hot ) than the bottom wall (T cold ). The temperature ratio (R θ = T hot /T cold ) is fixed at 1.01, 2 and 3 to study the effects of property variations at low Mach number. Results indicate that average and turbulent fields undergo significant changes. Compared with isothermal flow with constant viscosity, we observe that turbulence is enhanced in the cold side of the channel, characterized by locally lower viscosity whereas a decrease of turbulent kinetic energy is found at the hot wall. The turbulent structures near the cold wall are very short and densely populated vortices but near the hot wall there seems to be a long streaky structure or large elongated vortices. Spectral study reveals that turbulence is completely suppressed at the hot side of the channel at a large temperature ratio because no inertial zone is obtained (i.e. index of Kolmogorov scaling law is zero) from the spectra in these region.

  13. The interprocess NIR sampling as an alternative approach to multivariate statistical process control for identifying sources of product-quality variability.

    Science.gov (United States)

    Marković, Snežana; Kerč, Janez; Horvat, Matej

    2017-03-01

    We are presenting a new approach of identifying sources of variability within a manufacturing process by NIR measurements of samples of intermediate material after each consecutive unit operation (interprocess NIR sampling technique). In addition, we summarize the development of a multivariate statistical process control (MSPC) model for the production of enteric-coated pellet product of the proton-pump inhibitor class. By developing provisional NIR calibration models, the identification of critical process points yields comparable results to the established MSPC modeling procedure. Both approaches are shown to lead to the same conclusion, identifying parameters of extrusion/spheronization and characteristics of lactose that have the greatest influence on the end-product's enteric coating performance. The proposed approach enables quicker and easier identification of variability sources during manufacturing process, especially in cases when historical process data is not straightforwardly available. In the presented case the changes of lactose characteristics are influencing the performance of the extrusion/spheronization process step. The pellet cores produced by using one (considered as less suitable) lactose source were on average larger and more fragile, leading to consequent breakage of the cores during subsequent fluid bed operations. These results were confirmed by additional experimental analyses illuminating the underlying mechanism of fracture of oblong pellets during the pellet coating process leading to compromised film coating.

  14. Statistical evaluation of the performance of gridded monthly precipitation products from reanalysis data, satellite estimates, and merged analyses over China

    Science.gov (United States)

    Deng, Xueliang; Nie, Suping; Deng, Weitao; Cao, Weihua

    2018-04-01

    In this study, we compared the following four different gridded monthly precipitation products: the National Centers for Environmental Prediction version 2 (NCEP-2) reanalysis data, the satellite-based Climate Prediction Center Morphing technique (CMORPH) data, the merged satellite-gauge Global Precipitation Climatology Project (GPCP) data, and the merged satellite-gauge-model data from the Beijing Climate Center Merged Estimation of Precipitation (BMEP). We evaluated the performances of these products using monthly precipitation observations spanning the period of January 2003 to December 2013 from a dense, national, rain gauge network in China. Our assessment involved several statistical techniques, including spatial pattern, temporal variation, bias, root-mean-square error (RMSE), and correlation coefficient (CC) analysis. The results show that NCEP-2, GPCP, and BMEP generally overestimate monthly precipitation at the national scale and CMORPH underestimates it. However, all of the datasets successfully characterized the northwest to southeast increase in the monthly precipitation over China. Because they include precipitation gauge information from the Global Telecommunication System (GTS) network, GPCP and BMEP have much smaller biases, lower RMSEs, and higher CCs than NCEP-2 and CMORPH. When the seasonal and regional variations are considered, NCEP-2 has a larger error over southern China during the summer. CMORPH poorly reproduces the magnitude of the precipitation over southeastern China and the temporal correlation over western and northwestern China during all seasons. BMEP has a lower RMSE and higher CC than GPCP over eastern and southern China, where the station network is dense. In contrast, BMEP has a lower CC than GPCP over western and northwestern China, where the gauge network is relatively sparse.

  15. Combining the Power of Statistical Analyses and Community Interviews to Identify Adoption Barriers for Stormwater Best-Management Practices

    Science.gov (United States)

    Hoover, F. A.; Bowling, L. C.; Prokopy, L. S.

    2015-12-01

    Urban stormwater is an on-going management concern in municipalities of all sizes. In both combined or separated sewer systems, pollutants from stormwater runoff enter the natural waterway system during heavy rain events. Urban flooding during frequent and more intense storms are also a growing concern. Therefore, stormwater best-management practices (BMPs) are being implemented in efforts to reduce and manage stormwater pollution and overflow. The majority of BMP water quality studies focus on the small-scale, individual effects of the BMP, and the change in water quality directly from the runoff of these infrastructures. At the watershed scale, it is difficult to establish statistically whether or not these BMPs are making a difference in water quality, given that watershed scale monitoring is often costly and time consuming, relying on significant sources of funds, which a city may not have. Hence, there is a need to quantify the level of sampling needed to detect the water quality impact of BMPs at the watershed scale. In this study, a power analysis was performed on data from an urban watershed in Lafayette, Indiana, to determine the frequency of sampling required to detect a significant change in water quality measurements. Using the R platform, results indicate that detecting a significant change in watershed level water quality would require hundreds of weekly measurements, even when improvement is present. The second part of this study investigates whether the difficulty in demonstrating water quality change represents a barrier to adoption of stormwater BMPs. Semi-structured interviews of community residents and organizations in Chicago, IL are being used to investigate residents understanding of water quality and best management practices and identify their attitudes and perceptions towards stormwater BMPs. Second round interviews will examine how information on uncertainty in water quality improvements influences their BMP attitudes and perceptions.

  16. Statistical properties of interval mapping methods on quantitative trait loci location: impact on QTL/eQTL analyses

    Directory of Open Access Journals (Sweden)

    Wang Xiaoqiang

    2012-04-01

    Full Text Available Abstract Background Quantitative trait loci (QTL detection on a huge amount of phenotypes, like eQTL detection on transcriptomic data, can be dramatically impaired by the statistical properties of interval mapping methods. One of these major outcomes is the high number of QTL detected at marker locations. The present study aims at identifying and specifying the sources of this bias, in particular in the case of analysis of data issued from outbred populations. Analytical developments were carried out in a backcross situation in order to specify the bias and to propose an algorithm to control it. The outbred population context was studied through simulated data sets in a wide range of situations. The likelihood ratio test was firstly analyzed under the "one QTL" hypothesis in a backcross population. Designs of sib families were then simulated and analyzed using the QTL Map software. On the basis of the theoretical results in backcross, parameters such as the population size, the density of the genetic map, the QTL effect and the true location of the QTL, were taken into account under the "no QTL" and the "one QTL" hypotheses. A combination of two non parametric tests - the Kolmogorov-Smirnov test and the Mann-Whitney-Wilcoxon test - was used in order to identify the parameters that affected the bias and to specify how much they influenced the estimation of QTL location. Results A theoretical expression of the bias of the estimated QTL location was obtained for a backcross type population. We demonstrated a common source of bias under the "no QTL" and the "one QTL" hypotheses and qualified the possible influence of several parameters. Simulation studies confirmed that the bias exists in outbred populations under both the hypotheses of "no QTL" and "one QTL" on a linkage group. The QTL location was systematically closer to marker locations than expected, particularly in the case of low QTL effect, small population size or low density of markers, i

  17. Cost and quality effectiveness of objective-based and statistically-based quality control for volatile organic compounds analyses of gases

    International Nuclear Information System (INIS)

    Bennett, J.T.; Crowder, C.A.; Connolly, M.J.

    1994-01-01

    Gas samples from drums of radioactive waste at the Department of Energy (DOE) Idaho National Engineering Laboratory are being characterized for 29 volatile organic compounds to determine the feasibility of storing the waste in DOE's Waste Isolation Pilot Plant (WIPP) in Carlsbad, New Mexico. Quality requirements for the gas chromatography (GC) and GC/mass spectrometry chemical methods used to analyze the waste are specified in the Quality Assurance Program Plan for the WIPP Experimental Waste Characterization Program. Quality requirements consist of both objective criteria (data quality objectives, DQOs) and statistical criteria (process control). The DQOs apply to routine sample analyses, while the statistical criteria serve to determine and monitor precision and accuracy (P ampersand A) of the analysis methods and are also used to assign upper confidence limits to measurement results close to action levels. After over two years and more than 1000 sample analyses there are two general conclusions concerning the two approaches to quality control: (1) Objective criteria (e.g., ± 25% precision, ± 30% accuracy) based on customer needs and the usually prescribed criteria for similar EPA- approved methods are consistently attained during routine analyses. (2) Statistical criteria based on short term method performance are almost an order of magnitude more stringent than objective criteria and are difficult to satisfy following the same routine laboratory procedures which satisfy the objective criteria. A more cost effective and representative approach to establishing statistical method performances criteria would be either to utilize a moving average of P ampersand A from control samples over a several month time period or to determine within a sample variation by one-way analysis of variance of several months replicate sample analysis results or both. Confidence intervals for results near action levels could also be determined by replicate analysis of the sample in

  18. Process informed accurate compact modelling of 14-nm FinFET variability and application to statistical 6T-SRAM simulations

    OpenAIRE

    Wang, Xingsheng; Reid, Dave; Wang, Liping; Millar, Campbell; Burenkov, Alex; Evanschitzky, Peter; Baer, Eberhard; Lorenz, Juergen; Asenov, Asen

    2016-01-01

    This paper presents a TCAD based design technology co-optimization (DTCO) process for 14nm SOI FinFET based SRAM, which employs an enhanced variability aware compact modeling approach that fully takes process and lithography simulations and their impact on 6T-SRAM layout into account. Realistic double patterned gates and fins and their impacts are taken into account in the development of the variability-aware compact model. Finally, global process induced variability and local statistical var...

  19. Statistical parametric mapping and statistical probabilistic anatomical mapping analyses of basal/acetazolamide Tc-99m ECD brain SPECT for efficacy assessment of endovascular stent placement for middle cerebral artery stenosis

    International Nuclear Information System (INIS)

    Lee, Tae-Hong; Kim, Seong-Jang; Kim, In-Ju; Kim, Yong-Ki; Kim, Dong-Soo; Park, Kyung-Pil

    2007-01-01

    Statistical parametric mapping (SPM) and statistical probabilistic anatomical mapping (SPAM) were applied to basal/acetazolamide Tc-99m ECD brain perfusion SPECT images in patients with middle cerebral artery (MCA) stenosis to assess the efficacy of endovascular stenting of the MCA. Enrolled in the study were 11 patients (8 men and 3 women, mean age 54.2 ± 6.2 years) who had undergone endovascular stent placement for MCA stenosis. Using SPM and SPAM analyses, we compared the number of significant voxels and cerebral counts in basal and acetazolamide SPECT images before and after stenting, and assessed the perfusion changes and cerebral vascular reserve index (CVRI). The numbers of hypoperfusion voxels in SPECT images were decreased from 10,083 ± 8,326 to 4,531 ± 5,091 in basal images (P 0.0317) and from 13,398 ± 14,222 to 7,699 ± 10,199 in acetazolamide images (P = 0.0142) after MCA stenting. On SPAM analysis, the increases in cerebral counts were significant in acetazolamide images (90.9 ± 2.2 to 93.5 ± 2.3, P = 0.0098) but not in basal images (91 ± 2.7 to 92 ± 2.6, P = 0.1602). The CVRI also showed a statistically significant increase from before stenting (median 0.32; 95% CI -2.19-2.37) to after stenting (median 1.59; 95% CI -0.85-4.16; P = 0.0068). This study revealed the usefulness of voxel-based analysis of basal/acetazolamide brain perfusion SPECT after MCA stent placement. This study showed that SPM and SPAM analyses of basal/acetazolamide Tc-99m brain SPECT could be used to evaluate the short-term hemodynamic efficacy of successful MCA stent placement. (orig.)

  20. Recent hydrological variability and extreme precipitation events in Moroccan Middle-Atlas mountains: micro-scale analyses of lacustrine sediments

    Science.gov (United States)

    Jouve, Guillaume; Vidal, Laurence; Adallal, Rachid; Bard, Edouard; Benkaddour, Abdel; Chapron, Emmanuel; Courp, Thierry; Dezileau, Laurent; Hébert, Bertil; Rhoujjati, Ali; Simonneau, Anaelle; Sonzogni, Corinne; Sylvestre, Florence; Tachikawa, Kazuyo; Viry, Elisabeth

    2016-04-01

    Since the 1990s, the Mediterranean basin undergoes an increase in precipitation events and extreme droughts likely to intensify in the XXI century, and whose origin is attributable to human activities since 1850 (IPCC, 2013). Regional climate models indicate a strengthening of flood episodes at the end of the XXI century in Morocco (Tramblay et al, 2012). To understand recent hydrological and paleohydrological variability in North Africa, our study focuses on the macro- and micro-scale analysis of sedimentary sequences from Lake Azigza (Moroccan Middle Atlas Mountains) covering the last few centuries. This lake is relevant since local site monitoring revealed that lake water table levels were correlated with precipitation regime (Adallal R., PhD Thesis in progress). The aim of our study is to distinguish sedimentary facies characteristic of low and high lake levels, in order to reconstruct past dry and wet periods during the last two hundred years. Here, we present results from sedimentological (lithology, grain size, microstructures under thin sections), geochemical (XRF) and physical (radiography) analyses on short sedimentary cores (64 cm long) taken into the deep basin of Lake Azigza (30 meters water depth). Cores have been dated (radionuclides 210Pb, 137Cs, and 14C dating). Two main facies were distinguished: one organic-rich facies composed of wood fragments, several reworked layers and characterized by Mn peaks; and a second facies composed of terrigenous clastic sediments, without wood nor reworked layers, and characterized by Fe, Ti, Si and K peaks. The first facies is interpreted as a high lake level stand. Indeed, the highest paleoshoreline is close to the vegetation, and steeper banks can increase the current velocity, allowing the transport of wood fragments in case of extreme precipitation events. Mn peaks are interpreted as Mn oxides precipitations under well-oxygenated deep waters after runoff events. The second facies is linked to periods of

  1. Interpreting the concordance statistic of a logistic regression model: relation to the variance and odds ratio of a continuous explanatory variable.

    Science.gov (United States)

    Austin, Peter C; Steyerberg, Ewout W

    2012-06-20

    When outcomes are binary, the c-statistic (equivalent to the area under the Receiver Operating Characteristic curve) is a standard measure of the predictive accuracy of a logistic regression model. An analytical expression was derived under the assumption that a continuous explanatory variable follows a normal distribution in those with and without the condition. We then conducted an extensive set of Monte Carlo simulations to examine whether the expressions derived under the assumption of binormality allowed for accurate prediction of the empirical c-statistic when the explanatory variable followed a normal distribution in the combined sample of those with and without the condition. We also examine the accuracy of the predicted c-statistic when the explanatory variable followed a gamma, log-normal or uniform distribution in combined sample of those with and without the condition. Under the assumption of binormality with equality of variances, the c-statistic follows a standard normal cumulative distribution function with dependence on the product of the standard deviation of the normal components (reflecting more heterogeneity) and the log-odds ratio (reflecting larger effects). Under the assumption of binormality with unequal variances, the c-statistic follows a standard normal cumulative distribution function with dependence on the standardized difference of the explanatory variable in those with and without the condition. In our Monte Carlo simulations, we found that these expressions allowed for reasonably accurate prediction of the empirical c-statistic when the distribution of the explanatory variable was normal, gamma, log-normal, and uniform in the entire sample of those with and without the condition. The discriminative ability of a continuous explanatory variable cannot be judged by its odds ratio alone, but always needs to be considered in relation to the heterogeneity of the population.

  2. Analysing the spatial patterns of livestock anthrax in Kazakhstan in relation to environmental factors: a comparison of local (Gi* and morphology cluster statistics

    Directory of Open Access Journals (Sweden)

    Ian T. Kracalik

    2012-11-01

    Full Text Available We compared a local clustering and a cluster morphology statistic using anthrax outbreaks in large (cattle and small (sheep and goats domestic ruminants across Kazakhstan. The Getis-Ord (Gi* statistic and a multidirectional optimal ecotope algorithm (AMOEBA were compared using 1st, 2nd and 3rd order Rook contiguity matrices. Multivariate statistical tests were used to evaluate the environmental signatures between clusters and non-clusters from the AMOEBA and Gi* tests. A logistic regression was used to define a risk surface for anthrax outbreaks and to compare agreement between clustering methodologies. Tests revealed differences in the spatial distribution of clusters as well as the total number of clusters in large ruminants for AMOEBA (n = 149 and for small ruminants (n = 9. In contrast, Gi* revealed fewer large ruminant clusters (n = 122 and more small ruminant clusters (n = 61. Significant environmental differences were found between groups using the Kruskall-Wallis and Mann- Whitney U tests. Logistic regression was used to model the presence/absence of anthrax outbreaks and define a risk surface for large ruminants to compare with cluster analyses. The model predicted 32.2% of the landscape as high risk. Approximately 75% of AMOEBA clusters corresponded to predicted high risk, compared with ~64% of Gi* clusters. In general, AMOEBA predicted more irregularly shaped clusters of outbreaks in both livestock groups, while Gi* tended to predict larger, circular clusters. Here we provide an evaluation of both tests and a discussion of the use of each to detect environmental conditions associated with anthrax outbreak clusters in domestic livestock. These findings illustrate important differences in spatial statistical methods for defining local clusters and highlight the importance of selecting appropriate levels of data aggregation.

  3. Inferring the origin of rare fruit distillates from compositional data using multivariate statistical analyses and the identification of new flavour constituents.

    Science.gov (United States)

    Mihajilov-Krstev, Tatjana M; Denić, Marija S; Zlatković, Bojan K; Stankov-Jovanović, Vesna P; Mitić, Violeta D; Stojanović, Gordana S; Radulović, Niko S

    2015-04-01

    In Serbia, delicatessen fruit alcoholic drinks are produced from autochthonous fruit-bearing species such as cornelian cherry, blackberry, elderberry, wild strawberry, European wild apple, European blueberry and blackthorn fruits. There are no chemical data on many of these and herein we analysed volatile minor constituents of these rare fruit distillates. Our second goal was to determine possible chemical markers of these distillates through a statistical/multivariate treatment of the herein obtained and previously reported data. Detailed chemical analyses revealed a complex volatile profile of all studied fruit distillates with 371 identified compounds. A number of constituents were recognised as marker compounds for a particular distillate. Moreover, 33 of them represent newly detected flavour constituents in alcoholic beverages or, in general, in foodstuffs. With the aid of multivariate analyses, these volatile profiles were successfully exploited to infer the origin of raw materials used in the production of these spirits. It was also shown that all fruit distillates possessed weak antimicrobial properties. It seems that the aroma of these highly esteemed wild-fruit spirits depends on the subtle balance of various minor volatile compounds, whereby some of them are specific to a certain type of fruit distillate and enable their mutual distinction. © 2014 Society of Chemical Industry.

  4. Assessing the suitability of summary data for two-sample Mendelian randomization analyses using MR-Egger regression: the role of the I2 statistic.

    Science.gov (United States)

    Bowden, Jack; Del Greco M, Fabiola; Minelli, Cosetta; Davey Smith, George; Sheehan, Nuala A; Thompson, John R

    2016-12-01

    : MR-Egger regression has recently been proposed as a method for Mendelian randomization (MR) analyses incorporating summary data estimates of causal effect from multiple individual variants, which is robust to invalid instruments. It can be used to test for directional pleiotropy and provides an estimate of the causal effect adjusted for its presence. MR-Egger regression provides a useful additional sensitivity analysis to the standard inverse variance weighted (IVW) approach that assumes all variants are valid instruments. Both methods use weights that consider the single nucleotide polymorphism (SNP)-exposure associations to be known, rather than estimated. We call this the `NO Measurement Error' (NOME) assumption. Causal effect estimates from the IVW approach exhibit weak instrument bias whenever the genetic variants utilized violate the NOME assumption, which can be reliably measured using the F-statistic. The effect of NOME violation on MR-Egger regression has yet to be studied. An adaptation of the I2 statistic from the field of meta-analysis is proposed to quantify the strength of NOME violation for MR-Egger. It lies between 0 and 1, and indicates the expected relative bias (or dilution) of the MR-Egger causal estimate in the two-sample MR context. We call it IGX2 . The method of simulation extrapolation is also explored to counteract the dilution. Their joint utility is evaluated using simulated data and applied to a real MR example. In simulated two-sample MR analyses we show that, when a causal effect exists, the MR-Egger estimate of causal effect is biased towards the null when NOME is violated, and the stronger the violation (as indicated by lower values of IGX2 ), the stronger the dilution. When additionally all genetic variants are valid instruments, the type I error rate of the MR-Egger test for pleiotropy is inflated and the causal effect underestimated. Simulation extrapolation is shown to substantially mitigate these adverse effects. We

  5. Increased intra-participant variability in children with autistic spectrum disorder: Evidence from single trial analyses of evoked EEG.

    Directory of Open Access Journals (Sweden)

    Elizabeth eMilne

    2011-03-01

    Full Text Available Intra-participant variability in clinical conditions such as autistic spectrum disorder (ASD is an important indicator of pathophysiological processing. The data reported here illustrate that trial-by-trial variability can be reliably measured from EEG, and that intra-participant EEG variability is significantly greater in those with ASD than in neuro-typical matched controls. EEG recorded at the scalp is a linear mixture of activity arising from muscle artifacts and numerous concurrent brain processes. To minimise these additional sources of variability, EEG data were subjected to two different methods of spatial filtering. (i The data were decomposed using infomax Independent Component Analysis (ICA, a method of blind source separation which un-mixes the EEG signal into components with maximally independent time-courses, and (ii a surface Laplacian transform was performed (Current Source Density interpolation in order to reduce the effects of volume conduction. Data are presented from thirteen high functioning adolescents with ASD without co-morbid ADHD, and twelve neuro-typical age- IQ- and gender-matched controls. Comparison of variability between the ASD and neuro-typical groups indicated that intra-participant variability of P1 latency and P1 amplitude was greater in the participants with ASD, and inter-trial α-band phase coherence was lower in the participants with ASD. These data support the suggestion that individuals with ASD are less able to synchronise the activity of stimulus-related cell assemblies than neuro-typical individuals, and provide empirical evidence in support of theories of increased neural noise in ASD.

  6. Insights into hydroclimatic variability of Southern California since 125 ka, from multi-proxy analyses of alpine lakes

    Science.gov (United States)

    Glover, K. C.; MacDonald, G. M.; Kirby, M.

    2016-12-01

    Hydroclimatic variability is especially important in California, a water-stressed and increasingly populous region. We assess the range of past hydroclimatic sensitivity and variability in the San Bernardino Mountains of Southern California based on 125 ka of lacustrine sediment records. Geochemistry, charcoal and pollen highlight periods of sustained moisture, aridity and sudden variability driven by orbital and oceanic variations. Marine Isotope Stage 3 (MIS 3) is one such period of greater moisture availability that lasted c. 30 kyr, with smaller-scale perturbations likely reflect North Atlantic Dansgaard-Oeschgar events. Past glacial periods, MIS 4 and MIS 2, display high-amplitude changes. These include periods of reduced forest cover that span millennia, indicating long-lasting aridity. Rapid forest expansion also occurs, marking sudden shifts towards wet conditions. Fire regimes have also changed in tandem with hydroclimate and vegetation. Higher-resolution analysis of the past 10 ka shows that Southern California hydroclimate was broadly similar to other regions of the Southwest and Great Basin, including an orbital and oceanic-driven wet Early Holocene, dry Mid-Holocene, and highly variable Late Holocene. Shorter-term pluvial conditions occur throughout the Holocene, with episodic moisture likely derived from a Pacific source.

  7. Simple Crosscutting Concerns Are Not So Simple : Analysing Variability in Large-Scale Idioms-Based Implementations

    NARCIS (Netherlands)

    Bruntink, M.; Van Deursen, A.; d’Hondt, M.; Tourwé, T.

    2007-01-01

    This paper describes a method for studying idioms-based implementations of crosscutting concerns, and our experiences with it in the context of a real-world, large-scale embedded software system. In particular, we analyse a seemingly simple concern, tracing, and show that it exhibits significant

  8. Thermal infrared imagery as a tool for analysing the variability of surface saturated areas at various temporal and spatial scales

    Science.gov (United States)

    Glaser, Barbara; Antonelli, Marta; Pfister, Laurent; Klaus, Julian

    2017-04-01

    Surface saturated areas are important for the on- and offset of hydrological connectivity within the hillslope-riparian-stream continuum. This is reflected in concepts such as variable contributing areas or critical source areas. However, we still lack a standardized method for areal mapping of surface saturation and for observing its spatiotemporal variability. Proof-of-concept studies in recent years have shown the potential of thermal infrared (TIR) imagery to record surface saturation dynamics at various temporal and spatial scales. Thermal infrared imagery is thus a promising alternative to conventional approaches, such as the squishy boot method or the mapping of vegetation. In this study we use TIR images to investigate the variability of surface saturated areas at different temporal and spatial scales in the forested Weierbach catchment (0.45 km2) in western Luxembourg. We took TIR images of the riparian zone with a hand-held FLIR infrared camera at fortnightly intervals over 18 months at nine different locations distributed over the catchment. Not all of the acquired images were suitable for a derivation of the surface saturated areas, as various factors influence the usability of the TIR images (e.g. temperature contrasts, shadows, fog). Nonetheless, we obtained a large number of usable images that provided a good insight into the dynamic behaviour of surface saturated areas at different scales. The images revealed how diverse the evolution of surface saturated areas can be throughout the hydrologic year. For some locations with similar morphology or topography we identified diverging saturation dynamics, while other locations with different morphology / topography showed more similar behaviour. Moreover, we were able to assess the variability of the dynamics of expansion / contraction of saturated areas within the single locations, which can help to better understand the mechanisms behind surface saturation development.

  9. How to Make Nothing Out of Something: Analyses of the Impact of Study Sampling and Statistical Interpretation in Misleading Meta-Analytic Conclusions

    Directory of Open Access Journals (Sweden)

    Michael Robert Cunningham

    2016-10-01

    Full Text Available The limited resource model states that self-control is governed by a relatively finite set of inner resources on which people draw when exerting willpower. Once self-control resources have been used up or depleted, they are less available for other self-control tasks, leading to a decrement in subsequent self-control success. The depletion effect has been studied for over 20 years, tested or extended in more than 600 studies, and supported in an independent meta-analysis (Hagger, Wood, Stiff, and Chatzisarantis, 2010. Meta-analyses are supposed to reduce bias in literature reviews. Carter, Kofler, Forster, and McCullough’s (2015 meta-analysis, by contrast, included a series of questionable decisions involving sampling, methods, and data analysis. We provide quantitative analyses of key sampling issues: exclusion of many of the best depletion studies based on idiosyncratic criteria and the emphasis on mini meta-analyses with low statistical power as opposed to the overall depletion effect. We discuss two key methodological issues: failure to code for research quality, and the quantitative impact of weak studies by novice researchers. We discuss two key data analysis issues: questionable interpretation of the results of trim and fill and funnel plot asymmetry test procedures, and the use and misinterpretation of the untested Precision Effect Test [PET] and Precision Effect Estimate with Standard Error (PEESE procedures. Despite these serious problems, the Carter et al. meta-analysis results actually indicate that there is a real depletion effect – contrary to their title.

  10. Implementation of a Model Output Statistics based on meteorological variable screening for short‐term wind power forecast

    DEFF Research Database (Denmark)

    Ranaboldo, Matteo; Giebel, Gregor; Codina, Bernat

    2013-01-01

    A combination of physical and statistical treatments to post‐process numerical weather predictions (NWP) outputs is needed for successful short‐term wind power forecasts. One of the most promising and effective approaches for statistical treatment is the Model Output Statistics (MOS) technique....... The proposed MOS performed well in both wind farms, and its forecasts compare positively with an actual operative model in use at Risø DTU and other MOS types, showing minimum BIAS and improving NWP power forecast of around 15% in terms of root mean square error. Further improvements could be obtained...

  11. Statistical optics

    Science.gov (United States)

    Goodman, J. W.

    This book is based on the thesis that some training in the area of statistical optics should be included as a standard part of any advanced optics curriculum. Random variables are discussed, taking into account definitions of probability and random variables, distribution functions and density functions, an extension to two or more random variables, statistical averages, transformations of random variables, sums of real random variables, Gaussian random variables, complex-valued random variables, and random phasor sums. Other subjects examined are related to random processes, some first-order properties of light waves, the coherence of optical waves, some problems involving high-order coherence, effects of partial coherence on imaging systems, imaging in the presence of randomly inhomogeneous media, and fundamental limits in photoelectric detection of light. Attention is given to deterministic versus statistical phenomena and models, the Fourier transform, and the fourth-order moment of the spectrum of a detected speckle image.

  12. MODELO ESTADÍSTICO PARA ASOCIAR VARIABLES DEL ALUMNO CON SU RENDIMIENTO ESCOLAR I STATISTICAL MODEL TO ASSOCIATE VARIABLES OF THE STUDENT WITH HIS SCHOOL PERFORMANCE

    Directory of Open Access Journals (Sweden)

    Ely Rosas

    2018-04-01

    Full Text Available The main objective of this study was to determine associations between categorical variables pertaining to the student and his school performance, at governmental schools of the municipalities Gómez and Marcano of Nueva Esparta state, by adjusting the effects of column partnership model. The investigation was correlational in nature, with field design, based on applications to a reality of the educational context. As main results, obtained by adjusting the model in reference, the variables associated with school performance in Gómez municipality were: recreational activities, frequent use of computer at home and the use of Internet outside home to do homework. While in Marcano Municipality, they were: to have Internet at home, the place where the student is watching videogames and the number of times he eats in the day. In both municipalities, the characteristics: good feeling of the student when going to school and mastering of mathematical operations, were also linked to school performance.

  13. Categorization of the trophic status of a hydroelectric power plant reservoir in the Brazilian Amazon by statistical analyses and fuzzy approaches.

    Science.gov (United States)

    da Costa Lobato, Tarcísio; Hauser-Davis, Rachel Ann; de Oliveira, Terezinha Ferreira; Maciel, Marinalva Cardoso; Tavares, Maria Regina Madruga; da Silveira, Antônio Morais; Saraiva, Augusto Cesar Fonseca

    2015-02-15

    The Amazon area has been increasingly suffering from anthropogenic impacts, especially due to the construction of hydroelectric power plant reservoirs. The analysis and categorization of the trophic status of these reservoirs are of interest to indicate man-made changes in the environment. In this context, the present study aimed to categorize the trophic status of a hydroelectric power plant reservoir located in the Brazilian Amazon by constructing a novel Water Quality Index (WQI) and Trophic State Index (TSI) for the reservoir using major ion concentrations and physico-chemical water parameters determined in the area and taking into account the sampling locations and the local hydrological regimes. After applying statistical analyses (factor analysis and cluster analysis) and establishing a rule base of a fuzzy system to these indicators, the results obtained by the proposed method were then compared to the generally applied Carlson and a modified Lamparelli trophic state index (TSI), specific for trophic regions. The categorization of the trophic status by the proposed fuzzy method was shown to be more reliable, since it takes into account the specificities of the study area, while the Carlson and Lamparelli TSI do not, and, thus, tend to over or underestimate the trophic status of these ecosystems. The statistical techniques proposed and applied in the present study, are, therefore, relevant in cases of environmental management and policy decision-making processes, aiding in the identification of the ecological status of water bodies. With this, it is possible to identify which factors should be further investigated and/or adjusted in order to attempt the recovery of degraded water bodies. Copyright © 2014 Elsevier B.V. All rights reserved.

  14. Thermal and mechanical analyses of the spent nuclear fuel disposal canister and its barriers according to the design variable change

    International Nuclear Information System (INIS)

    Kwon, Young Joo

    2006-03-01

    This work constitutes a summary of research and development made for design and dimensioning of the spent nuclear fuel disposal canister. Since the spent nuclear fuel disposal emits high temperature heats and much radiation, its careful treatment is required. For that, a long term (usually 10,000 years) safe repository for the spent nuclear fuel disposal should be secured. Usually this repository is expected to locate at a depth of 500m underground. Many various analyses should be performed to secure the structural safety of the canister. For past years, these analyses have been performed to develop the canister model (so-called DKC-1 model). The diameter of the designed KDC-1 canister model is D=102m. However, there still remain some structural evaluations to make sure the structural safety of the designed KDC-1 canister mode. The one is the structural safety evaluation of the canister for the falling accident in the repository while handling the canister. There may happen two typical falling accidents in the repository. The one is the falling accident of the canister in the borehole while depositing the canister into the borehole. In these falling accidents the collision impact force between the canister and the surface of the ground or the bottom of the borehole may cause the structural damage onto the canister. However, the canister should be designed to withstand this impact force. Hence, the structural analysis of the canister for this impact force is required to guarantee the structural safety of the canister for this falling accident. Therefore in this report, the structural analyses of the KDC-1 canister model of the diameter of 102cm for two types of falling accidents are carried out for the impact forces while the canister collides onto the surface of the ground or the bottom of the borehole. The nonlinear structural analyses are performed for the canister to get the accurate analysis results assuming the materials composing canister parts as elasto

  15. Region-of-interest analyses of one-dimensional biomechanical trajectories: bridging 0D and 1D theory, augmenting statistical power

    Directory of Open Access Journals (Sweden)

    Todd C. Pataky

    2016-11-01

    Full Text Available One-dimensional (1D kinematic, force, and EMG trajectories are often analyzed using zero-dimensional (0D metrics like local extrema. Recently whole-trajectory 1D methods have emerged in the literature as alternatives. Since 0D and 1D methods can yield qualitatively different results, the two approaches may appear to be theoretically distinct. The purposes of this paper were (a to clarify that 0D and 1D approaches are actually just special cases of a more general region-of-interest (ROI analysis framework, and (b to demonstrate how ROIs can augment statistical power. We first simulated millions of smooth, random 1D datasets to validate theoretical predictions of the 0D, 1D and ROI approaches and to emphasize how ROIs provide a continuous bridge between 0D and 1D results. We then analyzed a variety of public datasets to demonstrate potential effects of ROIs on biomechanical conclusions. Results showed, first, that a priori ROI particulars can qualitatively affect the biomechanical conclusions that emerge from analyses and, second, that ROIs derived from exploratory/pilot analyses can detect smaller biomechanical effects than are detectable using full 1D methods. We recommend regarding ROIs, like data filtering particulars and Type I error rate, as parameters which can affect hypothesis testing results, and thus as sensitivity analysis tools to ensure arbitrary decisions do not influence scientific interpretations. Last, we describe open-source Python and MATLAB implementations of 1D ROI analysis for arbitrary experimental designs ranging from one-sample t tests to MANOVA.

  16. To what extent does variability of historical rainfall series influence extreme event statistics of sewer system surcharge and overflows?

    DEFF Research Database (Denmark)

    Schaarup-Jensen, Kjeld; Rasmussen, Michael R.; Thorndahl, Søren

    2008-01-01

    In urban drainage modeling long term extreme statistics has become an important basis for decision-making e.g. in connection with renovation projects. Therefore it is of great importance to minimize the uncertainties concerning long term prediction of maximum water levels and combined sewer...... overflow (CSO) in drainage systems. These uncertainties originate from large uncertainties regarding rainfall inputs, parameters, and assessment of return periods. This paper investigates how the choice of rainfall time series influences the extreme events statistics of max water levels in manholes and CSO...... gauges are located at a distance of max 20 kilometers from the catchment. All gauges are included in the Danish national rain gauge system which was launched in 1976. The paper describes to what extent the extreme events statistics based on these 9 series diverge from each other and how this diversity...

  17. To what extent does variability of historical rainfall series influence extreme event statistics of sewer system surcharge and overflows?

    DEFF Research Database (Denmark)

    Schaarup-Jensen, Kjeld; Rasmussen, Michael R.; Thorndahl, Søren

    2009-01-01

    In urban drainage modelling long term extreme statistics has become an important basis for decision-making e.g. in connection with renovation projects. Therefore it is of great importance to minimize the uncertainties concerning long term prediction of maximum water levels and combined sewer...... overflow (CSO) in drainage systems. These uncertainties originate from large uncertainties regarding rainfall inputs, parameters, and assessment of return periods. This paper investigates how the choice of rainfall time series influences the extreme events statistics of max water levels in manholes and CSO...... gauges are located at a distance of max 20 kilometers from the catchment. All gauges are included in the Danish national rain gauge system which was launched in 1976. The paper describes to what extent the extreme events statistics based on these 9 series diverge from each other and how this diversity...

  18. Comparative analyses of hydrological responses of two adjacent watersheds to climate variability and change using the SWAT model

    Science.gov (United States)

    Lee, Sangchul; Yeo, In-Young; Sadeghi, Ali M.; McCarty, Gregory W.; Hively, Wells; Lang, Megan W.; Sharifi, Amir

    2018-01-01

    Water quality problems in the Chesapeake Bay Watershed (CBW) are expected to be exacerbated by climate variability and change. However, climate impacts on agricultural lands and resultant nutrient loads into surface water resources are largely unknown. This study evaluated the impacts of climate variability and change on two adjacent watersheds in the Coastal Plain of the CBW, using the Soil and Water Assessment Tool (SWAT) model. We prepared six climate sensitivity scenarios to assess the individual impacts of variations in CO2concentration (590 and 850 ppm), precipitation increase (11 and 21 %), and temperature increase (2.9 and 5.0 °C), based on regional general circulation model (GCM) projections. Further, we considered the ensemble of five GCM projections (2085–2098) under the Representative Concentration Pathway (RCP) 8.5 scenario to evaluate simultaneous changes in CO2, precipitation, and temperature. Using SWAT model simulations from 2001 to 2014 as a baseline scenario, predicted hydrologic outputs (water and nitrate budgets) and crop growth were analyzed. Compared to the baseline scenario, a precipitation increase of 21 % and elevated CO2 concentration of 850 ppm significantly increased streamflow and nitrate loads by 50 and 52 %, respectively, while a temperature increase of 5.0 °C reduced streamflow and nitrate loads by 12 and 13 %, respectively. Crop biomass increased with elevated CO2 concentrations due to enhanced radiation- and water-use efficiency, while it decreased with precipitation and temperature increases. Over the GCM ensemble mean, annual streamflow and nitrate loads showed an increase of  ∼  70 % relative to the baseline scenario, due to elevated CO2 concentrations and precipitation increase. Different hydrological responses to climate change were observed from the two watersheds, due to contrasting land use and soil characteristics. The watershed with a larger percent of croplands demonstrated a greater

  19. Comparative analyses of hydrological responses of two adjacent watersheds to climate variability and change using the SWAT model

    Science.gov (United States)

    Lee, Sangchul; Yeo, In-Young; Sadeghi, Ali M.; McCarty, Gregory W.; Hively, Wells D.; Lang, Megan W.; Sharifi, Amir

    2018-01-01

    Water quality problems in the Chesapeake Bay Watershed (CBW) are expected to be exacerbated by climate variability and change. However, climate impacts on agricultural lands and resultant nutrient loads into surface water resources are largely unknown. This study evaluated the impacts of climate variability and change on two adjacent watersheds in the Coastal Plain of the CBW, using the Soil and Water Assessment Tool (SWAT) model. We prepared six climate sensitivity scenarios to assess the individual impacts of variations in CO2 concentration (590 and 850 ppm), precipitation increase (11 and 21 %), and temperature increase (2.9 and 5.0 °C), based on regional general circulation model (GCM) projections. Further, we considered the ensemble of five GCM projections (2085-2098) under the Representative Concentration Pathway (RCP) 8.5 scenario to evaluate simultaneous changes in CO2, precipitation, and temperature. Using SWAT model simulations from 2001 to 2014 as a baseline scenario, predicted hydrologic outputs (water and nitrate budgets) and crop growth were analyzed. Compared to the baseline scenario, a precipitation increase of 21 % and elevated CO2 concentration of 850 ppm significantly increased streamflow and nitrate loads by 50 and 52 %, respectively, while a temperature increase of 5.0 °C reduced streamflow and nitrate loads by 12 and 13 %, respectively. Crop biomass increased with elevated CO2 concentrations due to enhanced radiation- and water-use efficiency, while it decreased with precipitation and temperature increases. Over the GCM ensemble mean, annual streamflow and nitrate loads showed an increase of ˜ 70 % relative to the baseline scenario, due to elevated CO2 concentrations and precipitation increase. Different hydrological responses to climate change were observed from the two watersheds, due to contrasting land use and soil characteristics. The watershed with a larger percent of croplands demonstrated a greater increased rate of 5.2 kg N ha-1 in

  20. The use of mass spectrometry for analysing metabolite biomarkers in epidemiology: methodological and statistical considerations for application to large numbers of biological samples.

    Science.gov (United States)

    Lind, Mads V; Savolainen, Otto I; Ross, Alastair B

    2016-08-01

    Data quality is critical for epidemiology, and as scientific understanding expands, the range of data available for epidemiological studies and the types of tools used for measurement have also expanded. It is essential for the epidemiologist to have a grasp of the issues involved with different measurement tools. One tool that is increasingly being used for measuring biomarkers in epidemiological cohorts is mass spectrometry (MS), because of the high specificity and sensitivity of MS-based methods and the expanding range of biomarkers that can be measured. Further, the ability of MS to quantify many biomarkers simultaneously is advantageously compared to single biomarker methods. However, as with all methods used to measure biomarkers, there are a number of pitfalls to consider which may have an impact on results when used in epidemiology. In this review we discuss the use of MS for biomarker analyses, focusing on metabolites and their application and potential issues related to large-scale epidemiology studies, the use of MS "omics" approaches for biomarker discovery and how MS-based results can be used for increasing biological knowledge gained from epidemiological studies. Better understanding of the possibilities and possible problems related to MS-based measurements will help the epidemiologist in their discussions with analytical chemists and lead to the use of the most appropriate statistical tools for these data.

  1. Simultaneous assessment of phase chemistry, phase abundance and bulk chemistry with statistical electron probe micro-analyses: Application to cement clinkers

    Energy Technology Data Exchange (ETDEWEB)

    Wilson, William; Krakowiak, Konrad J.; Ulm, Franz-Josef, E-mail: ulm@mit.edu

    2014-01-15

    According to recent developments in cement clinker engineering, the optimization of chemical substitutions in the main clinker phases offers a promising approach to improve both reactivity and grindability of clinkers. Thus, monitoring the chemistry of the phases may become part of the quality control at the cement plants, along with the usual measurements of the abundance of the mineralogical phases (quantitative X-ray diffraction) and the bulk chemistry (X-ray fluorescence). This paper presents a new method to assess these three complementary quantities with a single experiment. The method is based on electron microprobe spot analyses, performed over a grid located on a representative surface of the sample and interpreted with advanced statistical tools. This paper describes the method and the experimental program performed on industrial clinkers to establish the accuracy in comparison to conventional methods. -- Highlights: •A new method of clinker characterization •Combination of electron probe technique with cluster analysis •Simultaneous assessment of phase abundance, composition and bulk chemistry •Experimental validation performed on industrial clinkers.

  2. Simultaneous assessment of phase chemistry, phase abundance and bulk chemistry with statistical electron probe micro-analyses: Application to cement clinkers

    International Nuclear Information System (INIS)

    Wilson, William; Krakowiak, Konrad J.; Ulm, Franz-Josef

    2014-01-01

    According to recent developments in cement clinker engineering, the optimization of chemical substitutions in the main clinker phases offers a promising approach to improve both reactivity and grindability of clinkers. Thus, monitoring the chemistry of the phases may become part of the quality control at the cement plants, along with the usual measurements of the abundance of the mineralogical phases (quantitative X-ray diffraction) and the bulk chemistry (X-ray fluorescence). This paper presents a new method to assess these three complementary quantities with a single experiment. The method is based on electron microprobe spot analyses, performed over a grid located on a representative surface of the sample and interpreted with advanced statistical tools. This paper describes the method and the experimental program performed on industrial clinkers to establish the accuracy in comparison to conventional methods. -- Highlights: •A new method of clinker characterization •Combination of electron probe technique with cluster analysis •Simultaneous assessment of phase abundance, composition and bulk chemistry •Experimental validation performed on industrial clinkers

  3. Chemical data and statistical analyses from a uranium hydrogeochemical survey of the Rio Ojo Caliente drainage basin, New Mexico. Part I. Water

    International Nuclear Information System (INIS)

    Wenrich-Verbeek, K.J.; Suits, V.J.

    1979-01-01

    This report presents the chemical analyses and statistical evaluation of 62 water samples collected in the north-central part of New Mexico near Rio Ojo Caliente. Both spring and surface-water samples were taken throughout the Rio Ojo Caliente drainage basin above and a few miles below the town of La Madera. A high U concentration (15 μg/l) found in the water of the Rio Ojo Caliente near La Madera, Rio Arriba County, New Mexico, during a regional sampling-technique study in August 1975 by the senior author, was investigated further in May 1976 to determine whether stream waters could be effectively used to trace the source of a U anomaly. A detailed study of the tributaries to the Rio Ojo Caliente, involving 29 samples, was conducted during a moderate discharge period, May 1976, so that small tributaries would contain water. This study isolated Canada de la Cueva as the tributary contributing the anomalous U, so that in May 1977, an extremely low discharge period due to the 1977 drought, an additional 33 samples were taken to further define the anomalous area. 6 references, 3 figures, 6 tables

  4. Variability in faecal egg counts – a statistical model to achieve reliable determination of anthelmintic resistance in livestock

    DEFF Research Database (Denmark)

    Nielsen, Martin Krarup; Vidyashankar, Anand N.; Hanlon, Bret

    statistical model was therefore developed for analysis of FECRT data from multiple farms. Horse age, gender, zip code and pre-treatment egg count were incorporated into the model. Horses and farms were kept as random effects. Resistance classifications were based on model-based 95% lower confidence limit (LCL...

  5. Multi-site study of diffusion metric variability: effects of site, vendor, field strength, and echo time on regions-of-interest and histogram-bin analyses.

    Science.gov (United States)

    Helmer, K G; Chou, M-C; Preciado, R I; Gimi, B; Rollins, N K; Song, A; Turner, J; Mori, S

    2016-02-27

    It is now common for magnetic-resonance-imaging (MRI) based multi-site trials to include diffusion-weighted imaging (DWI) as part of the protocol. It is also common for these sites to possess MR scanners of different manufacturers, different software and hardware, and different software licenses. These differences mean that scanners may not be able to acquire data with the same number of gradient amplitude values and number of available gradient directions. Variability can also occur in achievable b-values and minimum echo times. The challenge of a multi-site study then, is to create a common protocol by understanding and then minimizing the effects of scanner variability and identifying reliable and accurate diffusion metrics. This study describes the effect of site, scanner vendor, field strength, and TE on two diffusion metrics: the first moment of the diffusion tensor field (mean diffusivity, MD), and the fractional anisotropy (FA) using two common analyses (region-of-interest and mean-bin value of whole brain histograms). The goal of the study was to identify sources of variability in diffusion-sensitized imaging and their influence on commonly reported metrics. The results demonstrate that the site, vendor, field strength, and echo time all contribute to variability in FA and MD, though to different extent. We conclude that characterization of the variability of DTI metrics due to site, vendor, field strength, and echo time is a worthwhile step in the construction of multi-center trials.

  6. Estimation of time-variable fast flow path chemical concentrations for application in tracer-based hydrograph separation analyses

    Science.gov (United States)

    Kronholm, Scott C.; Capel, Paul D.

    2016-01-01

    Mixing models are a commonly used method for hydrograph separation, but can be hindered by the subjective choice of the end-member tracer concentrations. This work tests a new variant of mixing model that uses high-frequency measures of two tracers and streamflow to separate total streamflow into water from slowflow and fastflow sources. The ratio between the concentrations of the two tracers is used to create a time-variable estimate of the concentration of each tracer in the fastflow end-member. Multiple synthetic data sets, and data from two hydrologically diverse streams, are used to test the performance and limitations of the new model (two-tracer ratio-based mixing model: TRaMM). When applied to the synthetic streams under many different scenarios, the TRaMM produces results that were reasonable approximations of the actual values of fastflow discharge (±0.1% of maximum fastflow) and fastflow tracer concentrations (±9.5% and ±16% of maximum fastflow nitrate concentration and specific conductance, respectively). With real stream data, the TRaMM produces high-frequency estimates of slowflow and fastflow discharge that align with expectations for each stream based on their respective hydrologic settings. The use of two tracers with the TRaMM provides an innovative and objective approach for estimating high-frequency fastflow concentrations and contributions of fastflow water to the stream. This provides useful information for tracking chemical movement to streams and allows for better selection and implementation of water quality management strategies.

  7. Detecting relationships between the interannual variability in climate records and ecological time series using a multivariate statistical approach - four case studies for the North Sea region

    Energy Technology Data Exchange (ETDEWEB)

    Heyen, H. [GKSS-Forschungszentrum Geesthacht GmbH (Germany). Inst. fuer Gewaesserphysik

    1998-12-31

    A multivariate statistical approach is presented that allows a systematic search for relationships between the interannual variability in climate records and ecological time series. Statistical models are built between climatological predictor fields and the variables of interest. Relationships are sought on different temporal scales and for different seasons and time lags. The possibilities and limitations of this approach are discussed in four case studies dealing with salinity in the German Bight, abundance of zooplankton at Helgoland Roads, macrofauna communities off Norderney and the arrival of migratory birds on Helgoland. (orig.) [Deutsch] Ein statistisches, multivariates Modell wird vorgestellt, das eine systematische Suche nach potentiellen Zusammenhaengen zwischen Variabilitaet in Klima- und oekologischen Zeitserien erlaubt. Anhand von vier Anwendungsbeispielen wird der Klimaeinfluss auf den Salzgehalt in der Deutschen Bucht, Zooplankton vor Helgoland, Makrofauna vor Norderney, und die Ankunft von Zugvoegeln auf Helgoland untersucht. (orig.)

  8. Pearson's Correlation between Three Variables; Using Students' Basic Knowledge of Geometry for an Exercise in Mathematical Statistics

    Science.gov (United States)

    Vos, Pauline

    2009-01-01

    When studying correlations, how do the three bivariate correlation coefficients between three variables relate? After transforming Pearson's correlation coefficient r into a Euclidean distance, undergraduate students can tackle this problem using their secondary school knowledge of geometry (Pythagoras' theorem and similarity of triangles).…

  9. Uncertainties in repository performance from spatial variability of hydraulic conductivities - statistical estimation and stochastic simulation using PROPER

    International Nuclear Information System (INIS)

    Lovius, L.; Norman, S.; Kjellbert, N.

    1990-02-01

    An assessment has been made of the impact of spatial variability on the performance of a KBS-3 type repository. The uncertainties in geohydrologically related performance measures have been investigated using conductivity data from one of the Swedish study sites. The analysis was carried out with the PROPER code and the FSCF10 submodel. (authors)

  10. An MGF-based unified framework to determine the joint statistics of partial sums of ordered i.n.d. random variables

    KAUST Repository

    Nam, Sungsik

    2014-08-01

    The joint statistics of partial sums of ordered random variables (RVs) are often needed for the accurate performance characterization of a wide variety of wireless communication systems. A unified analytical framework to determine the joint statistics of partial sums of ordered independent and identically distributed (i.i.d.) random variables was recently presented. However, the identical distribution assumption may not be valid in several real-world applications. With this motivation in mind, we consider in this paper the more general case in which the random variables are independent but not necessarily identically distributed (i.n.d.). More specifically, we extend the previous analysis and introduce a new more general unified analytical framework to determine the joint statistics of partial sums of ordered i.n.d. RVs. Our mathematical formalism is illustrated with an application on the exact performance analysis of the capture probability of generalized selection combining (GSC)-based RAKE receivers operating over frequency-selective fading channels with a non-uniform power delay profile. © 1991-2012 IEEE.

  11. Accident Statistics

    Data.gov (United States)

    Department of Homeland Security — Accident statistics available on the Coast Guard’s website by state, year, and one variable to obtain tables and/or graphs. Data from reports has been loaded for...

  12. A statistical analysis of electrical cerebral activity; Contribution a l'etude de l'analyse statistique de l'activite electrique cerebrale

    Energy Technology Data Exchange (ETDEWEB)

    Bassant, Marie-Helene

    1971-01-15

    The aim of this work was to study the statistical properties of the amplitude of the electroencephalographic signal. The experimental method is described (implantation of electrodes, acquisition and treatment of data). The program of the mathematical analysis is given (calculation of probability density functions, study of stationarity) and the validity of the tests discussed. The results concerned ten rabbits. Trips of EEG were sampled during 40 s. with very short intervals (500 μs). The probability density functions established for different brain structures (especially the dorsal hippocampus) and areas, were compared during sleep, arousal and visual stimulus. Using a Χ{sup 2} test, it was found that the Gaussian distribution assumption was rejected in 96.7 per cent of the cases. For a given physiological state, there was no mathematical reason to reject the assumption of stationarity (in 96 per cent of the cases). (author) [French] Le but de ce travail est d'etudier les proprietes statistiques des amplitudes du signal electroencephalographique. La methode experimentale est decrite (implantation d'electrodes, acquisition et traitement des donnees). Le programme d'analyse mathematique est precise (calcul des courbes de repartition statistique, etude de la stationnarite du signal) et la validite des tests, discutee. Les resultats de l'etude portent sur 10 lapins. Des sequences de 40 s d'EEG sont echantillonnees. La valeur de la tension est prelevee a un pas d'echantillonnage de 500 μs. Les courbes de repartition statistiques sont comparees d'une region de l'encephale a l'autre (l'hippocampe dorsal a ete specialement analyse) ceci pendant le sommeil, l'eveil et des stimulations visuelles. Le test du Χ{sup 2} rejette l'hypothese de distribution normale dans 97 pour cent des cas. Pour un etat physiologique donne, il n'existe pas de raison mathematique a ce que soit repoussee l'hypothese de stationnarite, ceci dans 96.7 pour cent des cas. (auteur)

  13. Voxel-based statistical analysis of cerebral blood flow using Tc-99m ECD brain SPECT in patients with traumatic brain injury: group and individual analyses.

    Science.gov (United States)

    Shin, Yong Beom; Kim, Seong-Jang; Kim, In-Ju; Kim, Yong-Ki; Kim, Dong-Soo; Park, Jae Heung; Yeom, Seok-Ran

    2006-06-01

    Statistical parametric mapping (SPM) was applied to brain perfusion single photon emission computed tomography (SPECT) images in patients with traumatic brain injury (TBI) to investigate regional cerebral abnormalities compared to age-matched normal controls. Thirteen patients with TBI underwent brain perfusion SPECT were included in this study (10 males, three females, mean age 39.8 +/- 18.2, range 21 - 74). SPM2 software implemented in MATLAB 5.3 was used for spatial pre-processing and analysis and to determine the quantitative differences between TBI patients and age-matched normal controls. Three large voxel clusters of significantly decreased cerebral blood perfusion were found in patients with TBI. The largest clusters were area including medial frontal gyrus (voxel number 3642, peak Z-value = 4.31, 4.27, p = 0.000) in both hemispheres. The second largest clusters were areas including cingulated gyrus and anterior cingulate gyrus of left hemisphere (voxel number 381, peak Z-value = 3.67, 3.62, p = 0.000). Other clusters were parahippocampal gyrus (voxel number 173, peak Z-value = 3.40, p = 0.000) and hippocampus (voxel number 173, peak Z-value = 3.23, p = 0.001) in the left hemisphere. The false discovery rate (FDR) was less than 0.04. From this study, group and individual analyses of SPM2 could clearly identify the perfusion abnormalities of brain SPECT in patients with TBI. Group analysis of SPM2 showed hypoperfusion pattern in the areas including medial frontal gyrus of both hemispheres, cingulate gyrus, anterior cingulate gyrus, parahippocampal gyrus and hippocampus in the left hemisphere compared to age-matched normal controls. Also, left parahippocampal gyrus and left hippocampus were additional hypoperfusion areas. However, these findings deserve further investigation on a larger number of patients to be performed to allow a better validation of objective SPM analysis in patients with TBI.

  14. Statistical modeling methods to analyze the impacts of multiunit process variability on critical quality attributes of Chinese herbal medicine tablets.

    Science.gov (United States)

    Sun, Fei; Xu, Bing; Zhang, Yi; Dai, Shengyun; Yang, Chan; Cui, Xianglong; Shi, Xinyuan; Qiao, Yanjiang

    2016-01-01

    The quality of Chinese herbal medicine tablets suffers from batch-to-batch variability due to a lack of manufacturing process understanding. In this paper, the Panax notoginseng saponins (PNS) immediate release tablet was taken as the research subject. By defining the dissolution of five active pharmaceutical ingredients and the tablet tensile strength as critical quality attributes (CQAs), influences of both the manipulated process parameters introduced by an orthogonal experiment design and the intermediate granules' properties on the CQAs were fully investigated by different chemometric methods, such as the partial least squares, the orthogonal projection to latent structures, and the multiblock partial least squares (MBPLS). By analyzing the loadings plots and variable importance in the projection indexes, the granule particle sizes and the minimal punch tip separation distance in tableting were identified as critical process parameters. Additionally, the MBPLS model suggested that the lubrication time in the final blending was also important in predicting tablet quality attributes. From the calculated block importance in the projection indexes, the tableting unit was confirmed to be the critical process unit of the manufacturing line. The results demonstrated that the combinatorial use of different multivariate modeling methods could help in understanding the complex process relationships as a whole. The output of this study can then be used to define a control strategy to improve the quality of the PNS immediate release tablet.

  15. Statistical modeling methods to analyze the impacts of multiunit process variability on critical quality attributes of Chinese herbal medicine tablets

    Science.gov (United States)

    Sun, Fei; Xu, Bing; Zhang, Yi; Dai, Shengyun; Yang, Chan; Cui, Xianglong; Shi, Xinyuan; Qiao, Yanjiang

    2016-01-01

    The quality of Chinese herbal medicine tablets suffers from batch-to-batch variability due to a lack of manufacturing process understanding. In this paper, the Panax notoginseng saponins (PNS) immediate release tablet was taken as the research subject. By defining the dissolution of five active pharmaceutical ingredients and the tablet tensile strength as critical quality attributes (CQAs), influences of both the manipulated process parameters introduced by an orthogonal experiment design and the intermediate granules’ properties on the CQAs were fully investigated by different chemometric methods, such as the partial least squares, the orthogonal projection to latent structures, and the multiblock partial least squares (MBPLS). By analyzing the loadings plots and variable importance in the projection indexes, the granule particle sizes and the minimal punch tip separation distance in tableting were identified as critical process parameters. Additionally, the MBPLS model suggested that the lubrication time in the final blending was also important in predicting tablet quality attributes. From the calculated block importance in the projection indexes, the tableting unit was confirmed to be the critical process unit of the manufacturing line. The results demonstrated that the combinatorial use of different multivariate modeling methods could help in understanding the complex process relationships as a whole. The output of this study can then be used to define a control strategy to improve the quality of the PNS immediate release tablet. PMID:27932865

  16. Error correction and statistical analyses for intra-host comparisons of feline immunodeficiency virus diversity from high-throughput sequencing data.

    Science.gov (United States)

    Liu, Yang; Chiaromonte, Francesca; Ross, Howard; Malhotra, Raunaq; Elleder, Daniel; Poss, Mary

    2015-06-30

    Infection with feline immunodeficiency virus (FIV) causes an immunosuppressive disease whose consequences are less severe if cats are co-infected with an attenuated FIV strain (PLV). We use virus diversity measurements, which reflect replication ability and the virus response to various conditions, to test whether diversity of virulent FIV in lymphoid tissues is altered in the presence of PLV. Our data consisted of the 3' half of the FIV genome from three tissues of animals infected with FIV alone, or with FIV and PLV, sequenced by 454 technology. Since rare variants dominate virus populations, we had to carefully distinguish sequence variation from errors due to experimental protocols and sequencing. We considered an exponential-normal convolution model used for background correction of microarray data, and modified it to formulate an error correction approach for minor allele frequencies derived from high-throughput sequencing. Similar to accounting for over-dispersion in counts, this accounts for error-inflated variability in frequencies - and quite effectively reproduces empirically observed distributions. After obtaining error-corrected minor allele frequencies, we applied ANalysis Of VAriance (ANOVA) based on a linear mixed model and found that conserved sites and transition frequencies in FIV genes differ among tissues of dual and single infected cats. Furthermore, analysis of minor allele frequencies at individual FIV genome sites revealed 242 sites significantly affected by infection status (dual vs. single) or infection status by tissue interaction. All together, our results demonstrated a decrease in FIV diversity in bone marrow in the presence of PLV. Importantly, these effects were weakened or undetectable when error correction was performed with other approaches (thresholding of minor allele frequencies; probabilistic clustering of reads). We also queried the data for cytidine deaminase activity on the viral genome, which causes an asymmetric increase

  17. Statistical Diversions

    Science.gov (United States)

    Petocz, Peter; Sowey, Eric

    2012-01-01

    The term "data snooping" refers to the practice of choosing which statistical analyses to apply to a set of data after having first looked at those data. Data snooping contradicts a fundamental precept of applied statistics, that the scheme of analysis is to be planned in advance. In this column, the authors shall elucidate the…

  18. Practical Statistics

    CERN Document Server

    Lyons, L.

    2016-01-01

    Accelerators and detectors are expensive, both in terms of money and human effort. It is thus important to invest effort in performing a good statistical anal- ysis of the data, in order to extract the best information from it. This series of five lectures deals with practical aspects of statistical issues that arise in typical High Energy Physics analyses.

  19. Analysing temporal variability of particulate matter and possible contributing factors over Mahabaleshwar, a high-altitude station in Western Ghats, India

    Science.gov (United States)

    Leena, P. P.; Vijayakumar, K.; Anilkumar, V.; Pandithurai, G.

    2017-11-01

    Airborne particulate matter (PM) plays a vital role on climate change as well as human health. In the present study, temporal variability associated with mass concentrations of PM10, PM2.5, and PM1.0 were analysed using ground observations from Mahabaleswar (1348 m AMSL, 17.56 0N, 73.4 0E), a high-altitude station in the Western Ghats, India from June 2012 to May 2013. Concentrations of PM10, PM2.5, and PM1.0 showed strong diurnal, monthly, seasonal and weekday-weekend trends. The seasonal variation of PM1.0 and PM2.5 has showed highest concentrations during winter season compared to monsoon and pre-monsoon, but in the case of PM10 it showed highest concentrations in pre-monsoon season. Similarly, slightly higher PM concentrations were observed during weekends compared to weekdays. In addition, possible contributing factors to this temporal variability has been analysed based on the variation of secondary pollutants such as NO2, SO2, CO and O3 and long range transport of dust.

  20. Use of agricultural statistics to verify the interannual variability in land surface models: a case study over France with ISBA-A-gs

    Directory of Open Access Journals (Sweden)

    J.-C. Calvet

    2012-01-01

    Full Text Available In order to verify the interannual variability of the above-ground biomass of herbaceous vegetation simulated by the ISBA-A-gs land surface model, within the SURFEX modelling platform, French agricultural statistics for C3 crops and grasslands were compared with the simulations for the 1994–2008 period. While excellent correlations are obtained for grasslands, representing the interannual variability of crops is more difficult. It is shown that, the Maximum Available soil Water Capacity (MaxAWC has a large influence on the correlation between the model and the agricultural statistics. In particular, high values of MaxAWC tend to reduce the impact of the climate interannual variability on the simulated biomass. Also, high values of MaxAWC allow the simulation of a negative trend in biomass production, in relation to a marked warming trend, of about 0.12 Kyr−1 on average, affecting the daily maximum air temperature during the growing period (April–June. This trend is particularly acute in Northern France. The estimates of MaxAWC for C3 crops and grasslands, currently used in SURFEX, are about 129 mm and do not vary much. Therefore, more accurate grid-cell values of this parameter are needed.

  1. Statistical modeling methods to analyze the impacts of multiunit process variability on critical quality attributes of Chinese herbal medicine tablets

    Directory of Open Access Journals (Sweden)

    Sun F

    2016-11-01

    Full Text Available Fei Sun,1 Bing Xu,1,2 Yi Zhang,1 Shengyun Dai,1 Chan Yang,1 Xianglong Cui,1 Xinyuan Shi,1,2 Yanjiang Qiao1,2 1Research Center of Traditional Chinese Medicine Information Engineering, School of Chinese Materia Medica, Beijing University of Chinese Medicine, 2Key Laboratory of Manufacture Process Control and Quality Evaluation of Chinese Medicine, Beijing, People’s Republic of China Abstract: The quality of Chinese herbal medicine tablets suffers from batch-to-batch variability due to a lack of manufacturing process understanding. In this paper, the Panax notoginseng saponins (PNS immediate release tablet was taken as the research subject. By defining the dissolution of five active pharmaceutical ingredients and the tablet tensile strength as critical quality attributes (CQAs, influences of both the manipulated process parameters introduced by an orthogonal experiment design and the intermediate granules’ properties on the CQAs were fully investigated by different chemometric methods, such as the partial least squares, the orthogonal projection to latent structures, and the multiblock partial least squares (MBPLS. By analyzing the loadings plots and variable importance in the projection indexes, the granule particle sizes and the minimal punch tip separation distance in tableting were identified as critical process parameters. Additionally, the MBPLS model suggested that the lubrication time in the final blending was also important in predicting tablet quality attributes. From the calculated block importance in the projection indexes, the tableting unit was confirmed to be the critical process unit of the manufacturing line. The results demonstrated that the combinatorial use of different multivariate modeling methods could help in understanding the complex process relationships as a whole. The output of this study can then be used to define a control strategy to improve the quality of the PNS immediate release tablet. Keywords: Panax

  2. Substantial Variability Exists in Utilities' Nuclear Decommissioning Funding Adequacy: Baseline Trends (1997-2001); and Scenario and Sensitivity Analyses (Year 2001)

    International Nuclear Information System (INIS)

    Williams, D. G.

    2003-01-01

    This paper explores the trends over 1997-2001 in my baseline simulation analysis of the sufficiency of electric utilities' funds to eventually decommission the nation's nuclear power plants. Further, for 2001, I describe the utilities' funding adequacy results obtained using scenario and sensitivity analyses, respectively. In this paper, I focus more on the wide variability observed in these adequacy measures among utilities than on the results for the ''average'' utility in the nuclear industry. Only individual utilities, not average utilities -- often used by the nuclear industry to represent its funding adequacy -- will decommission their nuclear plants. Industry-wide results tend to mask the varied results for individual utilities. This paper shows that over 1997-2001, the variability of my baseline decommissioning funding adequacy measures (in percentages) for both utility fund balances and current contributions has remained very large, reflected in the sizable ranges and frequency distributions of these percentages. The relevance of this variability for nuclear decommissioning funding adequacy is, of course, focused more on those utilities that show below ideal balances and contribution levels. Looking backward, 42 of 67 utility fund (available) balances, in 2001, were above (and 25 below) their ideal baseline levels; in 1997, 42 of 76 were above (and 34 below) ideal levels. Of these, many utility balances were far above, and many far below, such ideal levels. The problem of certain utilities continuing to show balances much below ideal persists even with increases in the adequacy of ''average'' utility balances

  3. Fundamental statistical relationships between monthly and daily meteorological variables: Temporal downscaling of weather based on a global observational dataset

    Science.gov (United States)

    Sommer, Philipp; Kaplan, Jed

    2016-04-01

    Accurate modelling of large-scale vegetation dynamics, hydrology, and other environmental processes requires meteorological forcing on daily timescales. While meteorological data with high temporal resolution is becoming increasingly available, simulations for the future or distant past are limited by lack of data and poor performance of climate models, e.g., in simulating daily precipitation. To overcome these limitations, we may temporally downscale monthly summary data to a daily time step using a weather generator. Parameterization of such statistical models has traditionally been based on a limited number of observations. Recent developments in the archiving, distribution, and analysis of "big data" datasets provide new opportunities for the parameterization of a temporal downscaling model that is applicable over a wide range of climates. Here we parameterize a WGEN-type weather generator using more than 50 million individual daily meteorological observations, from over 10'000 stations covering all continents, based on the Global Historical Climatology Network (GHCN) and Synoptic Cloud Reports (EECRA) databases. Using the resulting "universal" parameterization and driven by monthly summaries, we downscale mean temperature (minimum and maximum), cloud cover, and total precipitation, to daily estimates. We apply a hybrid gamma-generalized Pareto distribution to calculate daily precipitation amounts, which overcomes much of the inability of earlier weather generators to simulate high amounts of daily precipitation. Our globally parameterized weather generator has numerous applications, including vegetation and crop modelling for paleoenvironmental studies.

  4. New Closed-Form Results on Ordered Statistics of Partial Sums of Gamma Random Variables and its Application to Performance Evaluation in the Presence of Nakagami Fading

    KAUST Repository

    Nam, Sung Sik

    2017-06-19

    Complex wireless transmission systems require multi-dimensional joint statistical techniques for performance evaluation. Here, we first present the exact closed-form results on order statistics of any arbitrary partial sums of Gamma random variables with the closedform results of core functions specialized for independent and identically distributed Nakagami-m fading channels based on a moment generating function-based unified analytical framework. These both exact closed-form results have never been published in the literature. In addition, as a feasible application example in which our new offered derived closed-form results can be applied is presented. In particular, we analyze the outage performance of the finger replacement schemes over Nakagami fading channels as an application of our method. Note that these analysis results are directly applicable to several applications, such as millimeter-wave communication systems in which an antenna diversity scheme operates using an finger replacement schemes-like combining scheme, and other fading scenarios. Note also that the statistical results can provide potential solutions for ordered statistics in any other research topics based on Gamma distributions or other advanced wireless communications research topics in the presence of Nakagami fading.

  5. Descriptive statistics.

    Science.gov (United States)

    Nick, Todd G

    2007-01-01

    Statistics is defined by the Medical Subject Headings (MeSH) thesaurus as the science and art of collecting, summarizing, and analyzing data that are subject to random variation. The two broad categories of summarizing and analyzing data are referred to as descriptive and inferential statistics. This chapter considers the science and art of summarizing data where descriptive statistics and graphics are used to display data. In this chapter, we discuss the fundamentals of descriptive statistics, including describing qualitative and quantitative variables. For describing quantitative variables, measures of location and spread, for example the standard deviation, are presented along with graphical presentations. We also discuss distributions of statistics, for example the variance, as well as the use of transformations. The concepts in this chapter are useful for uncovering patterns within the data and for effectively presenting the results of a project.

  6. Statistics of α-μ Random Variables and Their Applications inWireless Multihop Relaying and Multiple Scattering Channels

    KAUST Repository

    Wang, Kezhi

    2015-06-01

    Exact results for the probability density function (PDF) and cumulative distribution function (CDF) of the sum of ratios of products (SRP) and the sum of products (SP) of independent α-μ random variables (RVs) are derived. They are in the form of 1-D integral based on the existing works on the products and ratios of α-μ RVs. In the derivation, generalized Gamma (GG) ratio approximation (GGRA) is proposed to approximate SRP. Gamma ratio approximation (GRA) is proposed to approximate SRP and the ratio of sums of products (RSP). GG approximation (GGA) and Gamma approximation (GA) are used to approximate SP. The proposed results of the SRP can be used to calculate the outage probability (OP) for wireless multihop relaying systems or multiple scattering channels with interference. The proposed results of the SP can be used to calculate the OP for these systems without interference. In addition, the proposed approximate result of the RSP can be used to calculate the OP of the signal-To-interference ratio (SIR) in a multiple scattering system with interference. © 1967-2012 IEEE.

  7. Statistics of α-μ Random Variables and Their Applications inWireless Multihop Relaying and Multiple Scattering Channels

    KAUST Repository

    Wang, Kezhi; Wang, Tian; Chen, Yunfei; Alouini, Mohamed-Slim

    2015-01-01

    Exact results for the probability density function (PDF) and cumulative distribution function (CDF) of the sum of ratios of products (SRP) and the sum of products (SP) of independent α-μ random variables (RVs) are derived. They are in the form of 1-D integral based on the existing works on the products and ratios of α-μ RVs. In the derivation, generalized Gamma (GG) ratio approximation (GGRA) is proposed to approximate SRP. Gamma ratio approximation (GRA) is proposed to approximate SRP and the ratio of sums of products (RSP). GG approximation (GGA) and Gamma approximation (GA) are used to approximate SP. The proposed results of the SRP can be used to calculate the outage probability (OP) for wireless multihop relaying systems or multiple scattering channels with interference. The proposed results of the SP can be used to calculate the OP for these systems without interference. In addition, the proposed approximate result of the RSP can be used to calculate the OP of the signal-To-interference ratio (SIR) in a multiple scattering system with interference. © 1967-2012 IEEE.

  8. A Poisson Cluster Stochastic Rainfall Generator That Accounts for the Interannual Variability of Rainfall Statistics: Validation at Various Geographic Locations across the United States

    Directory of Open Access Journals (Sweden)

    Dongkyun Kim

    2014-01-01

    Full Text Available A novel approach for a Poisson cluster stochastic rainfall generator was validated in its ability to reproduce important rainfall and watershed response characteristics at 104 locations in the United States. The suggested novel approach, The Hybrid Model (THM, as compared to the traditional Poisson cluster rainfall modeling approaches, has an additional capability to account for the interannual variability of rainfall statistics. THM and a traditional approach of Poisson cluster rainfall model (modified Bartlett-Lewis rectangular pulse model were compared in their ability to reproduce the characteristics of extreme rainfall and watershed response variables such as runoff and peak flow. The results of the comparison indicate that THM generally outperforms the traditional approach in reproducing the distributions of peak rainfall, peak flow, and runoff volume. In addition, THM significantly outperformed the traditional approach in reproducing extreme rainfall by 2.3% to 66% and extreme flow values by 32% to 71%.

  9. A statistical, task-based evaluation method for three-dimensional x-ray breast imaging systems using variable-background phantoms

    International Nuclear Information System (INIS)

    Park, Subok; Jennings, Robert; Liu Haimo; Badano, Aldo; Myers, Kyle

    2010-01-01

    Purpose: For the last few years, development and optimization of three-dimensional (3D) x-ray breast imaging systems, such as digital breast tomosynthesis (DBT) and computed tomography, have drawn much attention from the medical imaging community, either academia or industry. However, there is still much room for understanding how to best optimize and evaluate the devices over a large space of many different system parameters and geometries. Current evaluation methods, which work well for 2D systems, do not incorporate the depth information from the 3D imaging systems. Therefore, it is critical to develop a statistically sound evaluation method to investigate the usefulness of inclusion of depth and background-variability information into the assessment and optimization of the 3D systems. Methods: In this paper, we present a mathematical framework for a statistical assessment of planar and 3D x-ray breast imaging systems. Our method is based on statistical decision theory, in particular, making use of the ideal linear observer called the Hotelling observer. We also present a physical phantom that consists of spheres of different sizes and materials for producing an ensemble of randomly varying backgrounds to be imaged for a given patient class. Lastly, we demonstrate our evaluation method in comparing laboratory mammography and three-angle DBT systems for signal detection tasks using the phantom's projection data. We compare the variable phantom case to that of a phantom of the same dimensions filled with water, which we call the uniform phantom, based on the performance of the Hotelling observer as a function of signal size and intensity. Results: Detectability trends calculated using the variable and uniform phantom methods are different from each other for both mammography and DBT systems. Conclusions: Our results indicate that measuring the system's detection performance with consideration of background variability may lead to differences in system performance

  10. Effect of chamber characteristics, loading and analysis time on motility and kinetic variables analysed with the CASA-mot system in goat sperm.

    Science.gov (United States)

    Del Gallego, R; Sadeghi, S; Blasco, E; Soler, C; Yániz, J L; Silvestre, M A

    2017-02-01

    Several factors unrelated to the semen samples could be influencing in the sperm motility analysis. The aim of the present research was to study the effect of four chambers with different characteristics, namely; slide-coverslip, Spermtrack, ISAS D4C10, and ISAS D4C20 on the sperm motility. The filling procedure (drop or capillarity) and analysis time (0, 120 and 240s), depth of chamber (10 or 20μm) and field on motility variables were analysed by use of the CASA-mot system in goat sperm. Use of the drop-filling chambers resulted in greater values than capillarity-filling chambers for all sperm motility and kinetic variables, except for LIN (64.5% compared with 56.3% of motility for drop- and capillarity-filling chambers respectively, PCASA-mot system with a drop-loaded chamber within 2min after filling the chamber. Copyright © 2016 Elsevier B.V. All rights reserved.

  11. Multivariate statistical methods a first course

    CERN Document Server

    Marcoulides, George A

    2014-01-01

    Multivariate statistics refer to an assortment of statistical methods that have been developed to handle situations in which multiple variables or measures are involved. Any analysis of more than two variables or measures can loosely be considered a multivariate statistical analysis. An introductory text for students learning multivariate statistical methods for the first time, this book keeps mathematical details to a minimum while conveying the basic principles. One of the principal strategies used throughout the book--in addition to the presentation of actual data analyses--is poin

  12. An analysis of the daily precipitation variability in the Himalayan orogen using a statistical parameterisation and its potential in driving landscape evolution models with stochastic climatic forcing

    Science.gov (United States)

    Deal, Eric; Braun, Jean

    2015-04-01

    A current challenge in landscape evolution modelling is to integrate realistic precipitation patterns and behaviour into longterm fluvial erosion models. The effect of precipitation on fluvial erosion can be subtle as well as nonlinear, implying that changes in climate (e.g. precipitation magnitude or storminess) may have unexpected outcomes in terms of erosion rates. For example Tucker and Bras (2000) show theoretically that changes in the variability of precipitation (storminess) alone can influence erosion rate across a landscape. To complicate the situation further, topography, ultimately driven by tectonic uplift but shaped by erosion, has a major influence on the distribution and style of precipitation. Therefore, in order to untangle the coupling between climate, erosion and tectonics in an actively uplifting orogen where fluvial erosion is dominant it is important to understand how the 'rain dial' used in a landscape evolution model (LEM) corresponds to real precipitation patterns. One issue with the parameterisation of rainfall for use in an LEM is the difference between the timescales for precipitation (≤ 1 year) and landscape evolution (> 103 years). As a result, precipitation patterns must be upscaled before being integrated into a model. The relevant question then becomes: What is the most appropriate measure of precipitation on a millennial timescale? Previous work (Tucker and Bras, 2000; Lague, 2005) has shown that precipitation can be properly upscaled by taking into account its variable nature, along with its average magnitude. This captures the relative size and frequency of extreme events, ensuring a more accurate characterisation of the integrated effects of precipitation on erosion over long periods of time. In light of this work, we present a statistical parameterisation that accurately models the mean and daily variability of ground based (APHRODITE) and remotely sensed (TRMM) precipitation data in the Himalayan orogen with only a few

  13. Statistical properties of coastal long waves analysed through sea-level time-gradient functions: exemplary analysis of the Siracusa, Italy, tide-gauge data

    Directory of Open Access Journals (Sweden)

    L. Bressan

    2016-01-01

    reconstructed sea level (RSL, the background slope (BS and the control function (CF. These functions are examined through a traditional spectral fast Fourier transform (FFT analysis and also through a statistical analysis, showing that they can be characterised by probability distribution functions PDFs such as the Student's t distribution (IS and RSL and the beta distribution (CF. As an example, the method has been applied to data from the tide-gauge station of Siracusa, Italy.

  14. Statistics Clinic

    Science.gov (United States)

    Feiveson, Alan H.; Foy, Millennia; Ploutz-Snyder, Robert; Fiedler, James

    2014-01-01

    Do you have elevated p-values? Is the data analysis process getting you down? Do you experience anxiety when you need to respond to criticism of statistical methods in your manuscript? You may be suffering from Insufficient Statistical Support Syndrome (ISSS). For symptomatic relief of ISSS, come for a free consultation with JSC biostatisticians at our help desk during the poster sessions at the HRP Investigators Workshop. Get answers to common questions about sample size, missing data, multiple testing, when to trust the results of your analyses and more. Side effects may include sudden loss of statistics anxiety, improved interpretation of your data, and increased confidence in your results.

  15. Comparative Analyses of Nonpathogenic, Opportunistic, and Totally Pathogenic Mycobacteria Reveal Genomic and Biochemical Variabilities and Highlight the Survival Attributes of Mycobacterium tuberculosis

    Science.gov (United States)

    Singh, Yadvir; Kohli, Sakshi; Ahmad, Javeed; Ehtesham, Nasreen Z.; Tyagi, Anil K.

    2014-01-01

    ABSTRACT Mycobacterial evolution involves various processes, such as genome reduction, gene cooption, and critical gene acquisition. Our comparative genome size analysis of 44 mycobacterial genomes revealed that the nonpathogenic (NP) genomes were bigger than those of opportunistic (OP) or totally pathogenic (TP) mycobacteria, with the TP genomes being smaller yet variable in size—their genomic plasticity reflected their ability to evolve and survive under various environmental conditions. From the 44 mycobacterial species, 13 species, representing TP, OP, and NP, were selected for genomic-relatedness analyses. Analysis of homologous protein-coding genes shared between Mycobacterium indicus pranii (NP), Mycobacterium intracellulare ATCC 13950 (OP), and Mycobacterium tuberculosis H37Rv (TP) revealed that 4,995 (i.e., ~95%) M. indicaus pranii proteins have homology with M. intracellulare, whereas the homologies among M. indicus pranii, M. intracellulare ATCC 13950, and M. tuberculosis H37Rv were significantly lower. A total of 4,153 (~79%) M. indicus pranii proteins and 4,093 (~79%) M. intracellulare ATCC 13950 proteins exhibited homology with the M. tuberculosis H37Rv proteome, while 3,301 (~82%) and 3,295 (~82%) M. tuberculosis H37Rv proteins showed homology with M. indicus pranii and M. intracellulare ATCC 13950 proteomes, respectively. Comparative metabolic pathway analyses of TP/OP/NP mycobacteria showed enzymatic plasticity between M. indicus pranii (NP) and M. intracellulare ATCC 13950 (OP), Mycobacterium avium 104 (OP), and M. tuberculosis H37Rv (TP). Mycobacterium tuberculosis seems to have acquired novel alternate pathways with possible roles in metabolism, host-pathogen interactions, virulence, and intracellular survival, and by implication some of these could be potential drug targets. PMID:25370496

  16. Monte Carlo Bayesian inference on a statistical model of sub-gridcolumn moisture variability using high-resolution cloud observations. Part 1: Method

    Science.gov (United States)

    Norris, Peter M.; da Silva, Arlindo M.

    2018-01-01

    A method is presented to constrain a statistical model of sub-gridcolumn moisture variability using high-resolution satellite cloud data. The method can be used for large-scale model parameter estimation or cloud data assimilation. The gridcolumn model includes assumed probability density function (PDF) intra-layer horizontal variability and a copula-based inter-layer correlation model. The observables used in the current study are Moderate Resolution Imaging Spectroradiometer (MODIS) cloud-top pressure, brightness temperature and cloud optical thickness, but the method should be extensible to direct cloudy radiance assimilation for a small number of channels. The algorithm is a form of Bayesian inference with a Markov chain Monte Carlo (MCMC) approach to characterizing the posterior distribution. This approach is especially useful in cases where the background state is clear but cloudy observations exist. In traditional linearized data assimilation methods, a subsaturated background cannot produce clouds via any infinitesimal equilibrium perturbation, but the Monte Carlo approach is not gradient-based and allows jumps into regions of non-zero cloud probability. The current study uses a skewed-triangle distribution for layer moisture. The article also includes a discussion of the Metropolis and multiple-try Metropolis versions of MCMC. PMID:29618847

  17. Monte Carlo Bayesian Inference on a Statistical Model of Sub-Gridcolumn Moisture Variability Using High-Resolution Cloud Observations. Part 1: Method

    Science.gov (United States)

    Norris, Peter M.; Da Silva, Arlindo M.

    2016-01-01

    A method is presented to constrain a statistical model of sub-gridcolumn moisture variability using high-resolution satellite cloud data. The method can be used for large-scale model parameter estimation or cloud data assimilation. The gridcolumn model includes assumed probability density function (PDF) intra-layer horizontal variability and a copula-based inter-layer correlation model. The observables used in the current study are Moderate Resolution Imaging Spectroradiometer (MODIS) cloud-top pressure, brightness temperature and cloud optical thickness, but the method should be extensible to direct cloudy radiance assimilation for a small number of channels. The algorithm is a form of Bayesian inference with a Markov chain Monte Carlo (MCMC) approach to characterizing the posterior distribution. This approach is especially useful in cases where the background state is clear but cloudy observations exist. In traditional linearized data assimilation methods, a subsaturated background cannot produce clouds via any infinitesimal equilibrium perturbation, but the Monte Carlo approach is not gradient-based and allows jumps into regions of non-zero cloud probability. The current study uses a skewed-triangle distribution for layer moisture. The article also includes a discussion of the Metropolis and multiple-try Metropolis versions of MCMC.

  18. Propensity-score matching in economic analyses: comparison with regression models, instrumental variables, residual inclusion, differences-in-differences, and decomposition methods.

    Science.gov (United States)

    Crown, William H

    2014-02-01

    This paper examines the use of propensity score matching in economic analyses of observational data. Several excellent papers have previously reviewed practical aspects of propensity score estimation and other aspects of the propensity score literature. The purpose of this paper is to compare the conceptual foundation of propensity score models with alternative estimators of treatment effects. References are provided to empirical comparisons among methods that have appeared in the literature. These comparisons are available for a subset of the methods considered in this paper. However, in some cases, no pairwise comparisons of particular methods are yet available, and there are no examples of comparisons across all of the methods surveyed here. Irrespective of the availability of empirical comparisons, the goal of this paper is to provide some intuition about the relative merits of alternative estimators in health economic evaluations where nonlinearity, sample size, availability of pre/post data, heterogeneity, and missing variables can have important implications for choice of methodology. Also considered is the potential combination of propensity score matching with alternative methods such as differences-in-differences and decomposition methods that have not yet appeared in the empirical literature.

  19. Meta-regression analyses to explain statistical heterogeneity in a systematic review of strategies for guideline implementation in primary health care.

    Directory of Open Access Journals (Sweden)

    Susanne Unverzagt

    Full Text Available This study is an in-depth-analysis to explain statistical heterogeneity in a systematic review of implementation strategies to improve guideline adherence of primary care physicians in the treatment of patients with cardiovascular diseases. The systematic review included randomized controlled trials from a systematic search in MEDLINE, EMBASE, CENTRAL, conference proceedings and registers of ongoing studies. Implementation strategies were shown to be effective with substantial heterogeneity of treatment effects across all investigated strategies. Primary aim of this study was to explain different effects of eligible trials and to identify methodological and clinical effect modifiers. Random effects meta-regression models were used to simultaneously assess the influence of multimodal implementation strategies and effect modifiers on physician adherence. Effect modifiers included the staff responsible for implementation, level of prevention and definition pf the primary outcome, unit of randomization, duration of follow-up and risk of bias. Six clinical and methodological factors were investigated as potential effect modifiers of the efficacy of different implementation strategies on guideline adherence in primary care practices on the basis of information from 75 eligible trials. Five effect modifiers were able to explain a substantial amount of statistical heterogeneity. Physician adherence was improved by 62% (95% confidence interval (95% CI 29 to 104% or 29% (95% CI 5 to 60% in trials where other non-medical professionals or nurses were included in the implementation process. Improvement of physician adherence was more successful in primary and secondary prevention of cardiovascular diseases by around 30% (30%; 95% CI -2 to 71% and 31%; 95% CI 9 to 57%, respectively compared to tertiary prevention. This study aimed to identify effect modifiers of implementation strategies on physician adherence. Especially the cooperation of different health

  20. Age and gender effects on normal regional cerebral blood flow studied using two different voxel-based statistical analyses; Effets de l'age et du genre sur la perfusion cerebrale regionale etudiee par deux methodes d'analyse statistique voxel-par-voxel

    Energy Technology Data Exchange (ETDEWEB)

    Pirson, A.S.; George, J.; Krug, B.; Vander Borght, T. [Universite Catholique de Louvain, Service de Medecine Nucleaire, Cliniques Universitaires de Mont-Godinne, Yvoir (Belgium); Van Laere, K. [Leuven Univ. Hospital, Nuclear Medicine Div. (Belgium); Jamart, J. [Universite Catholique de Louvain, Dept. de Biostatistiques, Cliniques Universitaires de Mont-Godinne, Yvoir (Belgium); D' Asseler, Y. [Ghent Univ., Medical Signal and Image Processing Dept. (MEDISIP), Faculty of applied sciences (Belgium); Minoshima, S. [Washington Univ., Dept. of Radiology, Seattle (United States)

    2009-10-15

    Fully automated analysis programs have been applied more and more to aid for the reading of regional cerebral blood flow SPECT study. They are increasingly based on the comparison of the patient study with a normal database. In this study, we evaluate the ability of Three-Dimensional Stereotactic Surface Projection (3 D-S.S.P.) to isolate effects of age and gender in a previously studied normal population. The results were also compared with those obtained using Statistical Parametric Mapping (S.P.M.99). Methods Eighty-nine {sup 99m}Tc-E.C.D.-SPECT studies performed in carefully screened healthy volunteers (46 females, 43 males; age 20 - 81 years) were analysed using 3 D-S.S.P.. A multivariate analysis based on the general linear model was performed with regions as intra-subject factor, gender as inter-subject factor and age as co-variate. Results Both age and gender had a significant interaction effect with regional tracer uptake. An age-related decline (p < 0.001) was found in the anterior cingulate gyrus, left frontal association cortex and left insula. Bilateral occipital association and left primary visual cortical uptake showed a significant relative increase with age (p < 0.001). Concerning the gender effect, women showed higher uptake (p < 0.01) in the parietal and right sensorimotor cortices. An age by gender interaction (p < 0.01) was only found in the left medial frontal cortex. The results were consistent with those obtained with S.P.M.99. Conclusion 3 D-S.S.P. analysis of normal r.C.B.F. variability is consistent with the literature and other automated voxel-based techniques, which highlight the effects of both age and gender. (authors)

  1. Discovery and characterisation of dietary patterns in two Nordic countries. Using non-supervised and supervised multivariate statistical techniques to analyse dietary survey data

    DEFF Research Database (Denmark)

    Edberg, Anna; Freyhult, Eva; Sand, Salomon

    - and inter-national data excerpts. For example, major PCA loadings helped deciphering both shared and disparate features, relating to food groups, across Danish and Swedish preschool consumers. Data interrogation, reliant on the above-mentioned composite techniques, disclosed one outlier dietary prototype...... prototype with the latter property was identified also in the Danish data material, but without low consumption of Vegetables or Fruit & berries. The second MDA-type of data interrogation involved Supervised Learning, also known as Predictive Modelling. These exercises involved the Random Forest (RF...... not elaborated on in-depth, output from several analyses suggests a preference for energy-based consumption data for Cluster Analysis and Predictive Modelling, over those appearing as weight....

  2. Application of multivariate statistical analyses in the interpretation of geochemical behaviour of uranium in phosphatic rocks in the Red Sea, Nile Valley and Western Desert, Egypt

    International Nuclear Information System (INIS)

    El-Arabi, A.M.Abd El-Gabar M.; Khalifa, Ibrahim H.

    2002-01-01

    Factor and cluster analyses as well as the Pearson correlation coefficient have been applied to geochemical data obtained from phosphorite and phosphatic rocks of Duwi Formation exposed at the Red Sea coast, Nile Valley and Western Desert. Sixty-six samples from a total of 71 collected samples were analysed for SiO 2 , TiO 2 , Al 2 O 3 , Fe 2 O 3 , CaO, MgO, Na 2 O, K 2 O, P 2 O 5 , Sr, U and Pb by XRF and their mineral constituents were determined by the use of XRD techniques. In addition, the natural radioactivity of the phosphatic samples due to their uranium, thorium and potassium contents was measured by gamma-spectrometry.The uranium content in the phosphate rocks with P 2 O 5 >15% (average of 106.6 ppm) is higher than in rocks with P 2 O 5 2 O 5 and CaO, whereas it is not related to changes in SiO 2 , TiO 2 , Al 2 O 3 , Fe 2 O 3 , MgO, Na 2 O and K 2 O concentrations.Factor analysis and the Pearson correlation coefficient revealed that uranium behaves geochemically in different ways in the phosphatic sediments and phosphorites in the Red Sea, Nile Valley and Western Desert. In the Red Sea and Western Desert phosphorites, uranium occurs mainly in oxidized U 6+ state where it seems to be fixed by the phosphate ion, forming secondary uranium phosphate minerals such as phosphuranylite.In the Nile Valley phosphorites, ionic substitution of Ca 2+ by U 4+ is the main controlling factor in the concentration of uranium in phosphate rocks. Moreover, fixation of U 6+ by phosphate ion and adsorption of uranium on phosphate minerals play subordinate roles

  3. Overview and statistical failure analyses of the electrical insulation system for the SSC long dipole magnets from an industrialization point of view

    International Nuclear Information System (INIS)

    Roach, J.F.

    1992-01-01

    The electrical insulation system of the SSC long dipole magnets is reviewed and potential dielectric failure modes discussed. Electrical insulation fabrication and assembly issues with respect to rate production manufacturability are addressed. The automation required for rate assembly of electrical insulation components will require critical online visual and dielectric screening tests to insure production quality. Storage and assembly areas must bc designed to prevent foreign particles from becoming entrapped in the insulation during critical coil winding, molding, and collaring operations. All hand assembly procedures involving dielectrics must be performed with rigorous attention to their impact on insulation integrity. Individual dipole magnets must have a sufficiently low probability of electrical insulation failure under all normal and fault mode voltage conditions such that the series of magnets in the SSC rings have acceptable Mean Time Between Failure (MTBF) with respect to dielectric mode failure events. Statistical models appropriate for large electrical system breakdown failure analysis are applied to the SSC magnet rings. The MTBF of the SSC system is related to failure data base for individual dipole magnet samples

  4. A graphical user interface (GUI) toolkit for the calculation of three-dimensional (3D) multi-phase biological effective dose (BED) distributions including statistical analyses.

    Science.gov (United States)

    Kauweloa, Kevin I; Gutierrez, Alonso N; Stathakis, Sotirios; Papanikolaou, Niko; Mavroidis, Panayiotis

    2016-07-01

    A toolkit has been developed for calculating the 3-dimensional biological effective dose (BED) distributions in multi-phase, external beam radiotherapy treatments such as those applied in liver stereotactic body radiation therapy (SBRT) and in multi-prescription treatments. This toolkit also provides a wide range of statistical results related to dose and BED distributions. MATLAB 2010a, version 7.10 was used to create this GUI toolkit. The input data consist of the dose distribution matrices, organ contour coordinates, and treatment planning parameters from the treatment planning system (TPS). The toolkit has the capability of calculating the multi-phase BED distributions using different formulas (denoted as true and approximate). Following the calculations of the BED distributions, the dose and BED distributions can be viewed in different projections (e.g. coronal, sagittal and transverse). The different elements of this toolkit are presented and the important steps for the execution of its calculations are illustrated. The toolkit is applied on brain, head & neck and prostate cancer patients, who received primary and boost phases in order to demonstrate its capability in calculating BED distributions, as well as measuring the inaccuracy and imprecision of the approximate BED distributions. Finally, the clinical situations in which the use of the present toolkit would have a significant clinical impact are indicated. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  5. An evaluation of the statistical variability in thermal expansion properties of steam generator tubesheet (SA-508) and tubing (Alloy-600TT)

    International Nuclear Information System (INIS)

    Riccardella, P.C.; Staples, J.F.; Kandra, J.T.

    2009-01-01

    Inspections of steam generator tubing are performed in U.S. PWRs as part of the Steam Generator Management Program. Westinghouse has recently completed a technical justification demonstrating that in steam generators with thermally treated Ni-Cr Alloy (Alloy 600TT) tubes that are hydraulically expanded into low alloy steel (SA-508) tubesheets, flaws in the region of the tubes below a certain distance from the top of the tubesheet, denoted H * , will not result in reactor coolant pressure boundary breach nor unacceptable primary-to-secondary leakage. This is because, even if a flaw in this region were to result in complete tube sever, if the length of undegraded tube in the tubesheet exceeds H*, neither operating nor accident loadings create sufficient pull-out forces to overcome the frictional forces between the tube and tubesheet. One key component of this technical justification is the differential thermal expansion between the tube and tubesheet, since a significant portion of the pullout strength of the hydraulically expanded tube-to-tubesheet joint is due to mechanical interference resulting from the larger expansion of the tubing relative to the tubesheet at a given temperature. To address this phenomenon, a detailed statistical evaluation of coefficient of thermal expansion (CTE) data for the tubesheet material (SA-508) and the tube material (thermally treated Alloy-600) was performed. Data used in the evaluation included existing test results obtained from a number of sources as well as extensive new laboratory data developed specifically for this purpose. The evaluation resulted in recommended statistical distributions of this property for the two materials including their means and probabilistic variability. In addition, it was determined that the CTE values reported in the ASME Code (Section II) represent reasonably conservative mean values for both the tubesheet and tubing material. (author)

  6. Statistical analyses of in-situ and soil-sample measurements for radionuclides in surface soil near the 116-K-2 trench

    International Nuclear Information System (INIS)

    Gilbert, R.O.; Klover, W.J.

    1988-09-01

    Radiation detection surveys are used at the US Department of Energy's Hanford Reservation near Richland, Washington, to determine areas that need posting as radiation zones or to measure dose rates in the field. The relationship between measurements made by Sodium Iodide (NaI) detectors mounted on the mobile Road Monitor vehicle and those made by hand-held GM P-11 probes and Micro-R meters are of particular interest because the Road Monitor can survey land areas in much less time than hand-held detectors. Statistical regression methods are used here to develop simple equations to predict GM P-11 probe gross gamma count-per-minute (cpm) and Micro-R-Meter μR/h measurements on the basis of NaI gross gamma count-per-second (cps) measurements obtained using the Road Monitor. These equations were estimated using data collected near the 116-K-2 Trench in the 100-K area on the Hanford Reservation. Equations are also obtained for estimating upper and lower limits within which the GM P-11 or Micro-R-Meter measurement corresponding to a given NaI Road Monitor measurement at a new location is expected to fall with high probability. An equation and limits for predicting GM P-11 measurements on the basis of Micro-R- Meter measurements is also estimated. Also, we estimate an equation that may be useful for approximating the 90 Sr measurement of a surface soil sample on the basis of a spectroscopy measurement for 137 Cs on that sample. 3 refs., 16 figs., 44 tabs

  7. Statistical inference

    CERN Document Server

    Rohatgi, Vijay K

    2003-01-01

    Unified treatment of probability and statistics examines and analyzes the relationship between the two fields, exploring inferential issues. Numerous problems, examples, and diagrams--some with solutions--plus clear-cut, highlighted summaries of results. Advanced undergraduate to graduate level. Contents: 1. Introduction. 2. Probability Model. 3. Probability Distributions. 4. Introduction to Statistical Inference. 5. More on Mathematical Expectation. 6. Some Discrete Models. 7. Some Continuous Models. 8. Functions of Random Variables and Random Vectors. 9. Large-Sample Theory. 10. General Meth

  8. Understanding Statistics - Cancer Statistics

    Science.gov (United States)

    Annual reports of U.S. cancer statistics including new cases, deaths, trends, survival, prevalence, lifetime risk, and progress toward Healthy People targets, plus statistical summaries for a number of common cancer types.

  9. A Combined Syntactical and Statistical Approach for R Peak Detection in Real-Time Long-Term Heart Rate Variability Analysis

    Directory of Open Access Journals (Sweden)

    David Pang

    2018-06-01

    Full Text Available Long-term heart rate variability (HRV analysis is useful as a noninvasive technique for autonomic nervous system activity assessment. It provides a method for assessing many physiological and pathological factors that modulate the normal heartbeat. The performance of HRV analysis systems heavily depends on a reliable and accurate detection of the R peak of the QRS complex. Ectopic beats caused by misdetection or arrhythmic events can introduce bias into HRV results, resulting in significant problems in their interpretation. This study presents a novel method for long-term detection of normal R peaks (which represent the normal heartbeat in electrocardiographic signals, intended specifically for HRV analysis. The very low computational complexity of the proposed method, which combines and exploits the advantages of syntactical and statistical approaches, enables real-time applications. The approach was validated using the Massachusetts Institute of Technology–Beth Israel Hospital Normal Sinus Rhythm and the Fantasia database, and has a sensitivity, positive predictivity, detection error rate, and accuracy of 99.998, 99.999, 0.003, and 99.996%, respectively.

  10. Holocene climate variability in arid Central Asia as revealed from high-resolution sedimentological and geochemical analyses of laminated sediments from Lake Chatyr Kol (Central Tian Shan, Kyrgyzstan)

    Science.gov (United States)

    Lauterbach, S.; Plessen, B.; Dulski, P.; Mingram, J.; Prasad, S.

    2013-12-01

    A pronounced trend from a predominantly wet climate during the early Holocene towards significantly drier conditions since the mid-Holocene, mainly attributed to the weakening of the Asian summer monsoon (ASM), is documented in numerous palaeoclimate records from the monsoon-influenced parts of Asia, e.g. the Tibetan Plateau and north- and southeastern China. In contrast, climate in the adjacent regions of mid-latitude arid Central Asia, located north and northwest of the Tibetan Plateau, is supposed to have been characterized by pronounced dry conditions during the early Holocene, wet conditions during the mid-Holocene and a rather moderate drying during the late Holocene, which is mainly attributed to the complex interplay between the mid-latitude Westerlies and the ASM. However, although mid-latitude Central Asia thus might represent a key region for the understanding of teleconnections between the ASM system and the Westerlies, knowledge about past climate development in this region is still ambiguous due to the limited number of high-resolution palaeoclimate records. Hence, new well-dated and highly resolved palaeoclimate records from this region are expected to provide important information about spatio-temporal changes in the regional interplay between Westerlies and ASM and thus aid the understanding of global climate teleconnections. As a part of the project CADY (Central Asian Climate Dynamics), aiming at reconstructing past climatic and hydrological variability in Central Asia, a sediment core of about 6.25 m length has been recovered from alpine Lake Chatyr Kol (40°36' N, 75°14' E, 3530 m a. s. l., surface area ~170 km2, maximum depth ~20 m), located in the Central Tian Shan of Kyrgyzstan. Sediment microfacies analysis on large-scale petrographic thin sections reveals continuously sub-mm scale laminated sediments throughout the record except for the uppermost ca. 60 cm. Microsedimentological characterization of these laminae, which are most probably

  11. Comparison of the Effects of Environmental Parameters on the Growth Variability of Vibrio parahaemolyticus Coupled with Strain Sources and Genotypes Analyses.

    Science.gov (United States)

    Liu, Bingxuan; Liu, Haiquan; Pan, Yingjie; Xie, Jing; Zhao, Yong

    2016-01-01

    Microbial growth variability plays an important role on food safety risk assessment. In this study, the growth kinetic characteristics corresponding to maximum specific growth rate (μmax) of 50 V. parahaemolyticus isolates from different sources and genotypes were evaluated at different temperatures (10, 20, 30, and 37°C) and salinity (0.5, 3, 5, 7, and 9%) using the automated turbidimetric system Bioscreen C. The results demonstrated that strain growth variability increased as the growth conditions became more stressful both in terms of temperature and salinity. The coefficient of variation (CV) of μmax for temperature was larger than that for salinity, indicating that the impact of temperature on strain growth variability was greater than that of salinity. The strains isolated from freshwater aquatic products had more conspicuous growth variations than those from seawater. Moreover, the strains with tlh (+) /tdh (+) /trh (-) exhibited higher growth variability than tlh (+) /tdh (-) /trh (-) or tlh (+) /tdh (-) /trh (+), revealing that gene heterogeneity might have possible relations with the growth variability. This research illustrates that the growth environments, strain sources as well as genotypes have impacts on strain growth variability of V. parahaemolyticus, which can be helpful for incorporating strain variability in predictive microbiology and microbial risk assessment.

  12. Monte Carlo Bayesian inference on a statistical model of sub-gridcolumn moisture variability using high-resolution cloud observations. Part 2: Sensitivity tests and results

    Science.gov (United States)

    Norris, Peter M.; da Silva, Arlindo M.

    2018-01-01

    Part 1 of this series presented a Monte Carlo Bayesian method for constraining a complex statistical model of global circulation model (GCM) sub-gridcolumn moisture variability using high-resolution Moderate Resolution Imaging Spectroradiometer (MODIS) cloud data, thereby permitting parameter estimation and cloud data assimilation for large-scale models. This article performs some basic testing of this new approach, verifying that it does indeed reduce mean and standard deviation biases significantly with respect to the assimilated MODIS cloud optical depth, brightness temperature and cloud-top pressure and that it also improves the simulated rotational–Raman scattering cloud optical centroid pressure (OCP) against independent (non-assimilated) retrievals from the Ozone Monitoring Instrument (OMI). Of particular interest, the Monte Carlo method does show skill in the especially difficult case where the background state is clear but cloudy observations exist. In traditional linearized data assimilation methods, a subsaturated background cannot produce clouds via any infinitesimal equilibrium perturbation, but the Monte Carlo approach allows non-gradient-based jumps into regions of non-zero cloud probability. In the example provided, the method is able to restore marine stratocumulus near the Californian coast, where the background state has a clear swath. This article also examines a number of algorithmic and physical sensitivities of the new method and provides guidance for its cost-effective implementation. One obvious difficulty for the method, and other cloud data assimilation methods as well, is the lack of information content in passive-radiometer-retrieved cloud observables on cloud vertical structure, beyond cloud-top pressure and optical thickness, thus necessitating strong dependence on the background vertical moisture structure. It is found that a simple flow-dependent correlation modification from Riishojgaard provides some help in this respect, by

  13. Monte Carlo Bayesian Inference on a Statistical Model of Sub-gridcolumn Moisture Variability Using High-resolution Cloud Observations . Part II; Sensitivity Tests and Results

    Science.gov (United States)

    da Silva, Arlindo M.; Norris, Peter M.

    2013-01-01

    Part I presented a Monte Carlo Bayesian method for constraining a complex statistical model of GCM sub-gridcolumn moisture variability using high-resolution MODIS cloud data, thereby permitting large-scale model parameter estimation and cloud data assimilation. This part performs some basic testing of this new approach, verifying that it does indeed significantly reduce mean and standard deviation biases with respect to the assimilated MODIS cloud optical depth, brightness temperature and cloud top pressure, and that it also improves the simulated rotational-Ramman scattering cloud optical centroid pressure (OCP) against independent (non-assimilated) retrievals from the OMI instrument. Of particular interest, the Monte Carlo method does show skill in the especially difficult case where the background state is clear but cloudy observations exist. In traditional linearized data assimilation methods, a subsaturated background cannot produce clouds via any infinitesimal equilibrium perturbation, but the Monte Carlo approach allows finite jumps into regions of non-zero cloud probability. In the example provided, the method is able to restore marine stratocumulus near the Californian coast where the background state has a clear swath. This paper also examines a number of algorithmic and physical sensitivities of the new method and provides guidance for its cost-effective implementation. One obvious difficulty for the method, and other cloud data assimilation methods as well, is the lack of information content in the cloud observables on cloud vertical structure, beyond cloud top pressure and optical thickness, thus necessitating strong dependence on the background vertical moisture structure. It is found that a simple flow-dependent correlation modification due to Riishojgaard (1998) provides some help in this respect, by better honoring inversion structures in the background state.

  14. Monte Carlo Bayesian Inference on a Statistical Model of Sub-Gridcolumn Moisture Variability Using High-Resolution Cloud Observations. Part 2: Sensitivity Tests and Results

    Science.gov (United States)

    Norris, Peter M.; da Silva, Arlindo M.

    2016-01-01

    Part 1 of this series presented a Monte Carlo Bayesian method for constraining a complex statistical model of global circulation model (GCM) sub-gridcolumn moisture variability using high-resolution Moderate Resolution Imaging Spectroradiometer (MODIS) cloud data, thereby permitting parameter estimation and cloud data assimilation for large-scale models. This article performs some basic testing of this new approach, verifying that it does indeed reduce mean and standard deviation biases significantly with respect to the assimilated MODIS cloud optical depth, brightness temperature and cloud-top pressure and that it also improves the simulated rotational-Raman scattering cloud optical centroid pressure (OCP) against independent (non-assimilated) retrievals from the Ozone Monitoring Instrument (OMI). Of particular interest, the Monte Carlo method does show skill in the especially difficult case where the background state is clear but cloudy observations exist. In traditional linearized data assimilation methods, a subsaturated background cannot produce clouds via any infinitesimal equilibrium perturbation, but the Monte Carlo approach allows non-gradient-based jumps into regions of non-zero cloud probability. In the example provided, the method is able to restore marine stratocumulus near the Californian coast, where the background state has a clear swath. This article also examines a number of algorithmic and physical sensitivities of the new method and provides guidance for its cost-effective implementation. One obvious difficulty for the method, and other cloud data assimilation methods as well, is the lack of information content in passive-radiometer-retrieved cloud observables on cloud vertical structure, beyond cloud-top pressure and optical thickness, thus necessitating strong dependence on the background vertical moisture structure. It is found that a simple flow-dependent correlation modification from Riishojgaard provides some help in this respect, by

  15. Beyond imperviousness: A statistical approach to identifying functional differences between development morphologies on variable source area-type response in urbanized watersheds

    Science.gov (United States)

    Lim, T. C.

    2016-12-01

    Empirical evidence has shown linkages between urbanization, hydrological regime change, and degradation of water quality and aquatic habitat. Percent imperviousness, has long been suggested as the dominant source of these negative changes. However, recent research identifying alternative pathways of runoff production at the watershed scale have called into question percent impervious surface area's primacy in urban runoff production compared to other aspects of urbanization including change in vegetative cover, imported water and water leakages, and the presence of drainage infrastructure. In this research I show how a robust statistical methodology can detect evidence of variable source area (VSA)-type hydrologic response associated with incremental hydraulic connectivity in watersheds. I then use logistic regression to explore how evidence of VSA-type response relates to the physical and meterological characteristics of the watershed. I find that impervious surface area is highly correlated with development, but does not add significant explanatory power beyond percent developed in predicting VSA-type response. Other aspects of development morphology, including percent developed open space and type of drainage infrastructure also do not add to the explanatory power of undeveloped land in predicting VSA-type response. Within only developed areas, the effect of developed open space was found to be more similar to that of total impervious area than to undeveloped land. These findings were consistent when tested across a national cross-section of urbanized watersheds, a higher resolution dataset of Baltimore Metropolitan Area watersheds, and a subsample of watersheds confirmed not to be served by combined sewer systems. These findings suggest that land development policies that focus on lot coverage should be revisited, and more focus should be placed on preserving native vegetation and soil conditions alongside development.

  16. Statistical ecology comes of age

    Science.gov (United States)

    Gimenez, Olivier; Buckland, Stephen T.; Morgan, Byron J. T.; Bez, Nicolas; Bertrand, Sophie; Choquet, Rémi; Dray, Stéphane; Etienne, Marie-Pierre; Fewster, Rachel; Gosselin, Frédéric; Mérigot, Bastien; Monestiez, Pascal; Morales, Juan M.; Mortier, Frédéric; Munoz, François; Ovaskainen, Otso; Pavoine, Sandrine; Pradel, Roger; Schurr, Frank M.; Thomas, Len; Thuiller, Wilfried; Trenkel, Verena; de Valpine, Perry; Rexstad, Eric

    2014-01-01

    The desire to predict the consequences of global environmental change has been the driver towards more realistic models embracing the variability and uncertainties inherent in ecology. Statistical ecology has gelled over the past decade as a discipline that moves away from describing patterns towards modelling the ecological processes that generate these patterns. Following the fourth International Statistical Ecology Conference (1–4 July 2014) in Montpellier, France, we analyse current trends in statistical ecology. Important advances in the analysis of individual movement, and in the modelling of population dynamics and species distributions, are made possible by the increasing use of hierarchical and hidden process models. Exciting research perspectives include the development of methods to interpret citizen science data and of efficient, flexible computational algorithms for model fitting. Statistical ecology has come of age: it now provides a general and mathematically rigorous framework linking ecological theory and empirical data. PMID:25540151

  17. Statistical ecology comes of age.

    Science.gov (United States)

    Gimenez, Olivier; Buckland, Stephen T; Morgan, Byron J T; Bez, Nicolas; Bertrand, Sophie; Choquet, Rémi; Dray, Stéphane; Etienne, Marie-Pierre; Fewster, Rachel; Gosselin, Frédéric; Mérigot, Bastien; Monestiez, Pascal; Morales, Juan M; Mortier, Frédéric; Munoz, François; Ovaskainen, Otso; Pavoine, Sandrine; Pradel, Roger; Schurr, Frank M; Thomas, Len; Thuiller, Wilfried; Trenkel, Verena; de Valpine, Perry; Rexstad, Eric

    2014-12-01

    The desire to predict the consequences of global environmental change has been the driver towards more realistic models embracing the variability and uncertainties inherent in ecology. Statistical ecology has gelled over the past decade as a discipline that moves away from describing patterns towards modelling the ecological processes that generate these patterns. Following the fourth International Statistical Ecology Conference (1-4 July 2014) in Montpellier, France, we analyse current trends in statistical ecology. Important advances in the analysis of individual movement, and in the modelling of population dynamics and species distributions, are made possible by the increasing use of hierarchical and hidden process models. Exciting research perspectives include the development of methods to interpret citizen science data and of efficient, flexible computational algorithms for model fitting. Statistical ecology has come of age: it now provides a general and mathematically rigorous framework linking ecological theory and empirical data.

  18. Variability and predictors of negative mood intensity in patients with borderline personality disorder and recurrent suicidal behavior: multilevel analyses applied to experience sampling methodology.

    Science.gov (United States)

    Nisenbaum, Rosane; Links, Paul S; Eynan, Rahel; Heisel, Marnin J

    2010-05-01

    Variability in mood swings is a characteristic of borderline personality disorder (BPD) and is associated with suicidal behavior. This study investigated patterns of mood variability and whether such patterns could be predicted from demographic and suicide-related psychological risk factors. Eighty-two adults with BPD and histories of recurrent suicidal behavior were recruited from 3 outpatient psychiatric programs in Canada. Experience sampling methodology (ESM) was used to assess negative mood intensity ratings on a visual analogue scale, 6 random times daily, for 21 days. Three-level models estimated variability between times (52.8%), days (22.2%), and patients (25.1%) and supported a quadratic pattern of daily mood variability. Depression scores predicted variability between patients' initial rating of the day. Average daily mood patterns depended on levels of hopelessness, suicide ideation, and sexual abuse history. Patients reporting moderate to severe sexual abuse and elevated suicide ideation were characterized by worsening moods from early morning up through evening, with little or no relief; patients reporting mild sexual abuse and low suicide ideation reported improved mood throughout the day. These patterns, if replicated in larger ESM studies, may potentially assist the clinician in determining which patients require close monitoring.

  19. Hydrogeologic characterization and evolution of the 'excavation damaged zone' by statistical analyses of pressure signals: application to galleries excavated at the clay-stone sites of Mont Terri (Ga98) and Tournemire (Ga03)

    International Nuclear Information System (INIS)

    Fatmi, H.; Ababou, R.; Matray, J.M.; Joly, C.

    2010-01-01

    Document available in extended abstract form only. This paper presents methods of statistical analysis and interpretation of hydrogeological signals in clayey formations, e.g., pore water pressure and atmospheric pressure. The purpose of these analyses is to characterize the hydraulic behaviour of this type of formation in the case of a deep repository of Mid- Level/High-Level and Long-lived radioactive wastes, and to study the evolution of the geologic formation and its EDZ (Excavation Damaged Zone) during the excavation of galleries. We focus on galleries Ga98 and Ga03 in the sites of Mont Terri (Jura, Switzerland) and Tournemire (France, Aveyron), through data collected in the BPP- 1 and PH2 boreholes, respectively. The Mont Terri site, crossing the Aalenian Opalinus clay-stone, is an underground laboratory managed by an international consortium, namely the Mont Terri project (Switzerland). The Tournemire site, crossing the Toarcian clay-stone, is an Underground Research facility managed by IRSN (France). We have analysed pore water and atmospheric pressure signals at these sites, sometimes in correlation with other data. The methods of analysis are based on the theory of stationary random signals (correlation functions, Fourier spectra, transfer functions, envelopes), and on multi-resolution wavelet analysis (adapted to nonstationary and evolutionary signals). These methods are also combined with filtering techniques, and they can be used for single signals as well as pairs of signals (cross-analyses). The objective of this work is to exploit pressure measurements in selected boreholes from the two compacted clay sites, in order to: - evaluate phenomena affecting the measurements (earth tides, barometric pressures..); - estimate hydraulic properties (specific storage..) of the clay-stones prior to excavation works and compare them with those estimated by pulse or slug tests on shorter time scales; - analyze the effects of drift excavation on pore pressures

  20. Application of a renormalization-group treatment to the statistical associating fluid theory for potentials of variable range (SAFT-VR).

    Science.gov (United States)

    Forte, Esther; Llovell, Felix; Vega, Lourdes F; Trusler, J P Martin; Galindo, Amparo

    2011-04-21

    An accurate prediction of phase behavior at conditions far and close to criticality cannot be accomplished by mean-field based theories that do not incorporate long-range density fluctuations. A treatment based on renormalization-group (RG) theory as developed by White and co-workers has proven to be very successful in improving the predictions of the critical region with different equations of state. The basis of the method is an iterative procedure to account for contributions to the free energy of density fluctuations of increasing wavelengths. The RG method has been combined with a number of versions of the statistical associating fluid theory (SAFT), by implementing White's earliest ideas with the improvements of Prausnitz and co-workers. Typically, this treatment involves two adjustable parameters: a cutoff wavelength L for density fluctuations and an average gradient of the wavelet function Φ. In this work, the SAFT-VR (variable range) equation of state is extended with a similar crossover treatment which, however, follows closely the most recent improvements introduced by White. The interpretation of White's latter developments allows us to establish a straightforward method which enables Φ to be evaluated; only the cutoff wavelength L then needs to be adjusted. The approach used here begins with an initial free energy incorporating only contributions from short-wavelength fluctuations, which are treated locally. The contribution from long-wavelength fluctuations is incorporated through an iterative procedure based on attractive interactions which incorporate the structure of the fluid following the ideas of perturbation theories and using a mapping that allows integration of the radial distribution function. Good agreement close and far from the critical region is obtained using a unique fitted parameter L that can be easily related to the range of the potential. In this way the thermodynamic properties of a square-well (SW) fluid are given by the same

  1. Statistical processing of experimental data

    OpenAIRE

    NAVRÁTIL, Pavel

    2012-01-01

    This thesis contains theory of probability and statistical sets. Solved and unsolved problems of probability, random variable and distributions random variable, random vector, statistical sets, regression and correlation analysis. Unsolved problems contains solutions.

  2. Ratio index variables or ANCOVA? Fisher's cats revisited.

    Science.gov (United States)

    Tu, Yu-Kang; Law, Graham R; Ellison, George T H; Gilthorpe, Mark S

    2010-01-01

    Over 60 years ago Ronald Fisher demonstrated a number of potential pitfalls with statistical analyses using ratio variables. Nonetheless, these pitfalls are largely overlooked in contemporary clinical and epidemiological research, which routinely uses ratio variables in statistical analyses. This article aims to demonstrate how very different findings can be generated as a result of less than perfect correlations among the data used to generate ratio variables. These imperfect correlations result from measurement error and random biological variation. While the former can often be reduced by improvements in measurement, random biological variation is difficult to estimate and eliminate in observational studies. Moreover, wherever the underlying biological relationships among epidemiological variables are unclear, and hence the choice of statistical model is also unclear, the different findings generated by different analytical strategies can lead to contradictory conclusions. Caution is therefore required when interpreting analyses of ratio variables whenever the underlying biological relationships among the variables involved are unspecified or unclear. (c) 2009 John Wiley & Sons, Ltd.

  3. Statistical analyses for the purpose of an early detection of global and regional climate change due to the anthropogenic greenhouse effect; Statistische Analysen zur Frueherkennung globaler und regionaler Klimaaenderungen aufgrund des anthropogenen Treibhauseffektes

    Energy Technology Data Exchange (ETDEWEB)

    Grieser, J.; Staeger, T.; Schoenwiese, C.D.

    2000-03-01

    The report answers the question where, why and how different climate variables have changed within the last 100 years. The analyzed variables are observed time series of temperature (mean, maximum, minimum), precipitation, air pressure, and water vapour pressure in a monthly resolution. The time series are given as station data and grid box data as well. Two kinds of time-series analysis are performed. The first is applied to find significant changes concerning mean and variance of the time series. Thereby also changes in the annual cycle and frequency of extreme events arise. The second approach is used to detect significant spatio-temporal patterns in the variations of climate variables, which are most likely driven by known natural and anthropogenic climate forcings. Furtheron, an estimation of climate noise allows to indicate regions where certain climate variables have changed significantly due to the enhanced anthropogenic greenhouse effect. (orig.) [German] Der Bericht gibt Antwort auf die Frage, wo sich welche Klimavariable wie und warum veraendert hat. Ausgangspunkt der Analyse sind huntertjaehrige Zeitreihen der Temperatur (Mittel, Maximum, Minimum), des Niederschlags, Luftdrucks und Wasserdampfpartialdrucks in monatlicher Aufloesung. Es wurden sowohl Stationsdaten als auch Gitterpunktdaten verwendet. Mit Hilfe der strukturorientierten Zeitreihenzerlegung wurden signifikankte Aenderungen im Mittel und in der Varianz der Zeitreihen gefunden. Diese betreffen auch Aenderungen im Jahresgang und in der Haeufigkeit extremer Ereignisse. Die ursachenorientierte Zeitreihenzerlegung selektiert signifikante raumzeitliche Variationen der Klimavariablen, die natuerlichen bzw. anthropogenen Klimaantrieben zugeordnet werden koennen. Eine Abschaetzung des Klimarauschens erlaubt darueber hinaus anzugeben, wo und wie signifikant der anthropogene Treibhauseffekt welche Klimavariablen veraendert hat. (orig.)

  4. Analyse spatiale et statistique de l’âge du Fer en France. L’exemple de la “ BaseFer ” Spatial and statistical analysis of the Iron Age in France. The example of 'basefer'

    Directory of Open Access Journals (Sweden)

    Olivier Buchsenschutz

    2009-05-01

    Full Text Available Le développement des systèmes d'information géographique (SIG permet d'introduire dans les bases de données archéologiques la localisation des données. Il est possible alors d'obtenir des cartes de répartition qu'il s'agit ensuite d'interpréter en s’appuyant sur des analyses statistiques et spatiales. Cartes et statistiques mettent en évidence l'état de la recherche, les conditions de conservation des sites, et au-delà des phénomènes historiques ou culturels.À travers un programme de recherche sur l'âge du Fer en France (Basefer une base de données globale a été constituée pour l'espace métropolitain. Cet article propose un certain nombre d'analyses sur les critères descriptifs généraux d’un corpus de 11 000 sites (les départements côtiers de la Méditerranée ne sont pas traités dans ce test. Le contrôle et le développement des rubriques plus fines seront réalisés avec une équipe élargie, avant une mise en réseau de la base.The development of Geographical Information Systems (GIS allows information in archaeological databases to be georeferenced. It is thus possible to obtain distribution maps which can then be interpreted using statistical and spatial analyses. Maps and statistics highlight the state of research, the condition of sites, and moreover historical and cultural phenomena.Through a research programme on the Iron Age in France (Basefer, a global database was established for the entire country. This article puts forward some analyses of the general descriptive criteria represented in a corpus of 11000 sites (departments along the Mediterranean Sea coast are excluded from this test. The control and development of finer descriptors will be undertaken by an enlarged team, before the data are networked.

  5. Renyi statistics in equilibrium statistical mechanics

    International Nuclear Information System (INIS)

    Parvan, A.S.; Biro, T.S.

    2010-01-01

    The Renyi statistics in the canonical and microcanonical ensembles is examined both in general and in particular for the ideal gas. In the microcanonical ensemble the Renyi statistics is equivalent to the Boltzmann-Gibbs statistics. By the exact analytical results for the ideal gas, it is shown that in the canonical ensemble, taking the thermodynamic limit, the Renyi statistics is also equivalent to the Boltzmann-Gibbs statistics. Furthermore it satisfies the requirements of the equilibrium thermodynamics, i.e. the thermodynamical potential of the statistical ensemble is a homogeneous function of first degree of its extensive variables of state. We conclude that the Renyi statistics arrives at the same thermodynamical relations, as those stemming from the Boltzmann-Gibbs statistics in this limit.

  6. Accounting for Unresolved Spatial Variability in Large Scale Models: Development and Evaluation of a Statistical Cloud Parameterization with Prognostic Higher Order Moments

    Energy Technology Data Exchange (ETDEWEB)

    Robert Pincus

    2011-05-17

    This project focused on the variability of clouds that is present across a wide range of scales ranging from the synoptic to the millimeter. In particular, there is substantial variability in cloud properties at scales smaller than the grid spacing of models used to make climate projections (GCMs) and weather forecasts. These models represent clouds and other small-scale processes with parameterizations that describe how those processes respond to and feed back on the largescale state of the atmosphere.

  7. Genetic variability and bottleneck analyses of Kanni adu goat population using microsatellite markers [Indian Veterinary Journal, 2015, 92(3): 24-27

    International Nuclear Information System (INIS)

    Thiruvenkadan, R.; Jeyakumar, M.; Saravana, R.; Periasamy, K.

    2016-01-01

    Full text: The genetic characterization and bottleneck analysis in Kodi Adu goat was done using 25 FAO recommended microsatellite markers. The mean observed number of alleles and polymorphism information content (PIC) were estimated to be 11.52±-0.95 and 0.817±0.023 respectively. The mean observed and expected equilibrium hyterozygosities were 0.660±0.045 and 0.846±0.018 respectively. The mean expected equilibrium gene diversity across 21 microsatellite loci under TAM, SMM and TPM were 0.793±0.028, 0.854±0.023 and 0.827±0.026 respectively. All the three statistical tests revealed significant deviation of Kodi Adu goats from mutation-drift equilibrium under the IAM and TPM model. The mode shift analysis supported the results under SMM indicating the absence of genetic bottleneck in the recent past in Kodi Adu goats. (author)

  8. Introduction of Transplant Registry Unified Management Program 2 (TRUMP2): scripts for TRUMP data analyses, part I (variables other than HLA-related data).

    Science.gov (United States)

    Atsuta, Yoshiko

    2016-01-01

    Collection and analysis of information on diseases and post-transplant courses of allogeneic hematopoietic stem cell transplant recipients have played important roles in improving therapeutic outcomes in hematopoietic stem cell transplantation. Efficient, high-quality data collection systems are essential. The introduction of the Second-Generation Transplant Registry Unified Management Program (TRUMP2) is intended to improve data quality and more efficient data management. The TRUMP2 system will also expand possible uses of data, as it is capable of building a more complex relational database. The construction of an accessible data utilization system for adequate data utilization by researchers would promote greater research activity. Study approval and management processes and authorship guidelines also need to be organized within this context. Quality control of processes for data manipulation and analysis will also affect study outcomes. Shared scripts have been introduced to define variables according to standard definitions for quality control and improving efficiency of registry studies using TRUMP data.

  9. Study of Glycemic Variability Through Time Series Analyses (Detrended Fluctuation Analysis and Poincaré Plot) in Children and Adolescents with Type 1 Diabetes.

    Science.gov (United States)

    García Maset, Leonor; González, Lidia Blasco; Furquet, Gonzalo Llop; Suay, Francisco Montes; Marco, Roberto Hernández

    2016-11-01

    Time series analysis provides information on blood glucose dynamics that is unattainable with conventional glycemic variability (GV) indices. To date, no studies have been published on these parameters in pediatric patients with type 1 diabetes. Our aim is to evaluate the relationship between time series analysis and conventional GV indices, and glycosylated hemoglobin (HbA1c) levels. This is a transversal study of 41 children and adolescents with type 1 diabetes. Glucose monitoring was carried out continuously for 72 h to study the following GV indices: standard deviation (SD) of glucose levels (mg/dL), coefficient of variation (%), interquartile range (IQR; mg/dL), mean amplitude of the largest glycemic excursions (MAGE), and continuous overlapping net glycemic action (CONGA). The time series analysis was conducted by means of detrended fluctuation analysis (DFA) and Poincaré plot. Time series parameters (DFA alpha coefficient and elements of the ellipse of the Poincaré plot) correlated well with the more conventional GV indices. Patients were grouped according to the terciles of these indices, to the terciles of eccentricity (1: 12.56-16.98, 2: 16.99-21.91, 3: 21.92-41.03), and to the value of the DFA alpha coefficient (> or ≤1.5). No differences were observed in the HbA1c of patients grouped by GV index criteria; however, significant differences were found in patients grouped by alpha coefficient and eccentricity, not only in terms of HbA1c, but also in SD glucose, IQR, and CONGA index. The loss of complexity in glycemic homeostasis is accompanied by an increase in variability.

  10. Introduction to Statistics

    Directory of Open Access Journals (Sweden)

    Mirjam Nielen

    2017-01-01

    Full Text Available Always wondered why research papers often present rather complicated statistical analyses? Or wondered how to properly analyse the results of a pragmatic trial from your own practice? This talk will give an overview of basic statistical principles and focus on the why of statistics, rather than on the how.This is a podcast of Mirjam's talk at the Veterinary Evidence Today conference, Edinburgh November 2, 2016. 

  11. An MGF-based unified framework to determine the joint statistics of partial sums of ordered i.n.d. random variables

    KAUST Repository

    Nam, Sungsik; Yang, Hongchuan; Alouini, Mohamed-Slim; Kim, Dongin

    2014-01-01

    framework to determine the joint statistics of partial sums of ordered i.n.d. RVs. Our mathematical formalism is illustrated with an application on the exact performance analysis of the capture probability of generalized selection combining (GSC)-based RAKE

  12. Consequences of kriging and land use regression for PM2.5 predictions in epidemiologic analyses: insights into spatial variability using high-resolution satellite data.

    Science.gov (United States)

    Alexeeff, Stacey E; Schwartz, Joel; Kloog, Itai; Chudnovsky, Alexandra; Koutrakis, Petros; Coull, Brent A

    2015-01-01

    Many epidemiological studies use predicted air pollution exposures as surrogates for true air pollution levels. These predicted exposures contain exposure measurement error, yet simulation studies have typically found negligible bias in resulting health effect estimates. However, previous studies typically assumed a statistical spatial model for air pollution exposure, which may be oversimplified. We address this shortcoming by assuming a realistic, complex exposure surface derived from fine-scale (1 km × 1 km) remote-sensing satellite data. Using simulation, we evaluate the accuracy of epidemiological health effect estimates in linear and logistic regression when using spatial air pollution predictions from kriging and land use regression models. We examined chronic (long-term) and acute (short-term) exposure to air pollution. Results varied substantially across different scenarios. Exposure models with low out-of-sample R(2) yielded severe biases in the health effect estimates of some models, ranging from 60% upward bias to 70% downward bias. One land use regression exposure model with >0.9 out-of-sample R(2) yielded upward biases up to 13% for acute health effect estimates. Almost all models drastically underestimated the SEs. Land use regression models performed better in chronic effect simulations. These results can help researchers when interpreting health effect estimates in these types of studies.

  13. Statistical thermodynamics

    International Nuclear Information System (INIS)

    Lim, Gyeong Hui

    2008-03-01

    This book consists of 15 chapters, which are basic conception and meaning of statistical thermodynamics, Maxwell-Boltzmann's statistics, ensemble, thermodynamics function and fluctuation, statistical dynamics with independent particle system, ideal molecular system, chemical equilibrium and chemical reaction rate in ideal gas mixture, classical statistical thermodynamics, ideal lattice model, lattice statistics and nonideal lattice model, imperfect gas theory on liquid, theory on solution, statistical thermodynamics of interface, statistical thermodynamics of a high molecule system and quantum statistics

  14. The Effect of Unequal Samples, Heterogeneity of Covariance Matrices, and Number of Variables on Discriminant Analysis Classification Tables and Related Statistics.

    Science.gov (United States)

    Spearing, Debra; Woehlke, Paula

    To assess the effect on discriminant analysis in terms of correct classification into two groups, the following parameters were systematically altered using Monte Carlo techniques: sample sizes; proportions of one group to the other; number of independent variables; and covariance matrices. The pairing of the off diagonals (or covariances) with…

  15. Methodological principles for the evaluation of impact of the variability and the climatic change in the human health, a statistical focus

    International Nuclear Information System (INIS)

    Ortiz Bulto, Paulo Lazaro; Vladimir Guevara, Antonio; Ulloa, Jacqueline; Aparicio, Marilyn

    2001-01-01

    Signal detection of climate variability or change and the evaluation of its specific effects, requires an understanding of the variations in the observed data, which describe the natural climate variability and change signals. It is also necessary to understand the complex interactions that make up the climate system. In the present work, an unusual methodological approach is taken to evaluate the effects and impacts of climate variability and change on the behaviour of different diseases, on the basis of practical experience of its application in four countries of the Caribbean, Central and South America: Cuba, Panama, Bolivia and Paraguay. For the determination of the climate signal change multivariate analysis techniques (empirical orthogonal functions) were used, combined with robust methods of time series decomposition (decomposition by median). They allowed us to describe the changes observed in the seasonal patterns of climate and epidemiological diseases for the period 1991-1999, with respect to the period 1961-1990. These results were used to build an autoregressive model with non-constant variance, with a climate index based on the signals obtained from the decompositions, which enters the model as an exogenous variable in order to make projections of the diseases

  16. THE STUDY ON THE EFFECT OF FORMULATION VARIABLES ON IN VITRO FLOATING TIME AND THE RELEASE PROPERTIES OF A FLOATING DRUG DELIVERY SYSTEM BY A STATISTICAL OPTIMIZATION TECHNIQUE

    Directory of Open Access Journals (Sweden)

    C. NARENDRA

    2008-03-01

    Full Text Available The present investigation concerns the evaluation of the effect of formulation variables on in vitro floating time and the release properties in developing a floating drug delivery system (FDDS containing a highly water soluble drug metoprolol tartrate (MT in the presence of a gas generating agent. A 32 full factorial design was employed in formulating the FDDS containing hydroxyl propylmethylcellulose (HPMC K4M and sodium carboxymethylcellulose (NaCMC as swellable polymers. Drug-to-polymer ratio and polymer-to-polymer ratio were included as independent variables. The main effect and the interaction terms were quantitatively evaluated by a quadratic model to predict formulations with the floating time desired, and the release properties. It was found that only drug-to-polymer ratio and its quadratic term were found to be significantly affective for all the response variables. Non-Fickian transport was confirmed as a release mechanism from the optimized formulations. The desirability function was used to optimize the response variables, each having a different target, and the observed responses were highly agreed with experimental values. The results demonstrate the feasibility of the model in the development of FDDS containing a highly water-soluble drug MT.

  17. The mean and the individual: Integrating variable-centered and person-centered analyses of cognitive recovery in patients with substance use disorders

    Directory of Open Access Journals (Sweden)

    Marsha E. Bates

    2013-12-01

    Full Text Available Neuropsychological and cognitive deficits are observed in the majority of persons with alcohol and drug use disorders and may interfere with treatment processes and outcomes. Although, on average, the brain and cognition improve with abstinence or markedly reduced substance use, better understanding of the heterogeneity in the time-course and extent of cognitive recovery at the individual level is useful to promote bench-to-bedside translation and inform clinical decision making. This study integrated a variable-centered and a person-centered approach to characterize diversity in cognitive recovery in 197 patients in treatment for a substance use disorder. We assessed executive function, verbal ability, memory, and complex information processing speed at treatment entry, and then 6, 26, and 52 weeks later. Structural equation modeling was used to define underlying ability constructs and determine the mean level of cognitive changes in the sample while minimizing measurement error and practice effects on specific tests. Individual-level empirical growth plots of latent factor scores were used to explore prototypical trajectories of cognitive change. At the level of the mean, small to medium effect size gains in cognitive abilities were observed over one year. At the level of the individual, the mean trajectory of change was also the modal individual recovery trajectory shown by about half the sample. Other prototypical cognitive change trajectories observed in all four cognitive domains included Delayed Gain, Loss of Gain, and Continuous Gain. Together these trajectories encompassed between 86% and 94% of individual growth plots across the four latent abilities. Further research is needed to replicate and predict trajectory membership. Replication of the present findings would have useful implications for targeted treatment planning and the new cognitive interventions being developed to enhance treatment outcomes.

  18. Effect of a brief cognitive behavioural intervention on criminal thinking and prison misconduct in male inmates: Variable-oriented and person-oriented analyses.

    Science.gov (United States)

    Walters, Glenn D

    2017-12-01

    There is some consensus on the value of cognitive-behaviourally informed interventions in the criminal justice system, but uncertainty about which components are of critical value. To test the hypothesis that change in prisoners - criminal thinking and institutional misconduct - will both follow completion of a brief cognitive behavioural intervention. A one-group pre-test-post-test quasi-experimental design was used to assess change on the General Criminal Thinking (GCT) scale of the Psychological Inventory of Criminal Thinking Styles among 219 male prisoners completing a 10-week cognitive behavioural intervention, referred to as 'Lifestyle Issues'. Institutional misconduct was measured for 1 year prior to completion of the course and 2 years subsequently. Using variable-oriented analysis, post-test GCT scores were compared with change in prison conduct, controlling for the pre-test thinking scores. Calculations were repeated by using person-oriented analysis. Prisoners who displayed a drop in GCT scores between pre-test and post-test levels were significantly more likely to show a reduction in prison misconduct, whereas prison misconduct was likely to escalate among those who displayed a rise in criminal thinking scores from pre-test to post-test. These findings must still be regarded as preliminary, but taken together with other work and with cognitive behavioural theory, they suggest that development of more prosocial thinking and abilities may have an early beneficial effect on institutional behaviour. Their measurement may offer a practical way in which men could be assessed for readiness to return to the community. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

  19. Global genetic analyses reveal strong inter-ethnic variability in the loss of activity of the organic cation transporter OCT1.

    Science.gov (United States)

    Seitz, Tina; Stalmann, Robert; Dalila, Nawar; Chen, Jiayin; Pojar, Sherin; Dos Santos Pereira, Joao N; Krätzner, Ralph; Brockmöller, Jürgen; Tzvetkov, Mladen V

    2015-01-01

    The organic cation transporter OCT1 (SLC22A1) mediates the uptake of vitamin B1, cationic drugs, and xenobiotics into hepatocytes. Nine percent of Caucasians lack or have very low OCT1 activity due to loss-of-function polymorphisms in OCT1 gene. Here we analyzed the global genetic variability in OCT1 to estimate the therapeutic relevance of OCT1 polymorphisms in populations beyond Caucasians and to identify evolutionary patterns of the common loss of OCT1 activity in humans. We applied massively parallel sequencing to screen for coding polymorphisms in 1,079 unrelated individuals from 53 populations worldwide. The obtained data was combined with the existing 1000 Genomes data comprising an additional 1,092 individuals from 14 populations. The identified OCT1 variants were characterized in vitro regarding their cellular localization and their ability to transport 10 known OCT1 substrates. Both the population genetics data and transport data were used in tandem to generate a world map of loss of OCT1 activity. We identified 16 amino acid substitutions potentially causing loss of OCT1 function and analyzed them together with five amino acid substitutions that were not expected to affect OCT1 function. The variants constituted 16 major alleles and 14 sub-alleles. Six major alleles showed improper subcellular localization leading to substrate-wide loss in activity. Five major alleles showed correct subcellular localization, but substrate-specific loss of activity. Striking differences were observed in the frequency of loss of OCT1 activity worldwide. While most East Asian and Oceanian individuals had completely functional OCT1, 80 % of native South American Indians lacked functional OCT1 alleles. In East Asia and Oceania the average nucleotide diversity of the loss-of-function variants was much lower than that of the variants that do not affect OCT1 function (ratio of 0.03) and was significantly lower than the theoretically expected heterozygosity (Tajima's D = -1

  20. Learning in artistic gymnastics. An experimental study with children analysing some variables in that process Aprendizaje en gimnasia artística. Un estudio experimental con niños que analiza ciertas variables del proceso

    Directory of Open Access Journals (Sweden)

    J. López

    2010-09-01

    Full Text Available

    Today the training of sports skills has lead to the conception of new approaches to attain maximum results. In practice, many teaching methods are used, yet most of the articles on motor learning or sports training refer to the total or global and the partial or analytic methods, both of interest in the field of gymnastics, offering a number of important combinations between either extreme.

    Opinions differ concerning effectiveness, and such differences also exist in gymnastics. Carrasco (1977, nevertheless, proposes "mini-circuits" as the ideal teaching method in gymnastics. In looking for a practical solution to global or analytical teaching, one experimental group study was undertaken with children participating in Sports Schools between the ages of 9 and 11. The aim was to compare the effect of three training sessions (analytical training, "mini-circuit" training, mixed training on the learning and recall of gymnastic skills.

    Interested in both final performance as well as the teaching process, the following variables were studied: motor activity time, waiting time, total number of global movements, total number of feedbacks emitted by the teacher (amount and direction, and total number of spot checks. A pre-test, post-test and re- test design was used with three groups to assess the three training sessions. Each group was trained to learn the same variable-dependent outcome.

    The results of the study showed that the "mini-circuit" training was the most effective learning and recall method. The most highly-influence process variables were both the type of aids and type of feedback provided. Overall, it is worth highlighting the importance of using the "mini-circuit" method with children. From a pedagogic perspective, this is an important finding to take into consideration, which could yield important results during schooling.
    KEY WORDS

  1. Statistical modelling for precision agriculture: A case study in optimal environmental schedules for Agaricus Bisporus production via variable domain functional regression

    Science.gov (United States)

    Panayi, Efstathios; Kyriakides, George

    2017-01-01

    Quantifying the effects of environmental factors over the duration of the growing process on Agaricus Bisporus (button mushroom) yields has been difficult, as common functional data analysis approaches require fixed length functional data. The data available from commercial growers, however, is of variable duration, due to commercial considerations. We employ a recently proposed regression technique termed Variable-Domain Functional Regression in order to be able to accommodate these irregular-length datasets. In this way, we are able to quantify the contribution of covariates such as temperature, humidity and water spraying volumes across the growing process, and for different lengths of growing processes. Our results indicate that optimal oxygen and temperature levels vary across the growing cycle and we propose environmental schedules for these covariates to optimise overall yields. PMID:28961254

  2. Structural analysis of GaN using high-resolution X-ray diffraction at variable temperatures; Analyse struktureller Eigenschaften von GaN mittels hochaufloesender Roentgenbeugung bei variabler Messtemperatur

    Energy Technology Data Exchange (ETDEWEB)

    Roder, C.

    2007-02-26

    The main topic of this thesis was the study of stress phenomena in GaN layers by application of high-resolution X-ray diffractometry at variable measurement temperature. For this a broad spectrum of different GaN samples was studied, which extended from bulk GaN crystals as well as thick c-plane oriented HVPE-GaN layers on c-plane sapphire over laterlaly overgrown c-plane GaN Layers on Si(111) substrates toon-polar a-plnae GaN layers on r-plane sapphire. The main topic of the measurements was the determination of the lattice parameters. Supplementarily the curvature of the waver as well as the excitonic resosance energies were studied by means of photoluminescence respectively photoreflection spectroscopy. By the measurement of the temperature-dependent lattice parameters of different GaN bulk crystals for the first time a closed set of thermal-expansion coefficients of GaN was determined from 12 to 1205 K with large accuracy. Analoguously the thermal-expansion coefficents of the substrate material sapphire were determinde over a temperature range from 10 to 1166 K.

  3. Boating Accident Statistics

    Data.gov (United States)

    Department of Homeland Security — Accident statistics available on the Coast Guard’s website by state, year, and one variable to obtain tables and/or graphs. Data from reports has been loaded for...

  4. Understanding advanced statistical methods

    CERN Document Server

    Westfall, Peter

    2013-01-01

    Introduction: Probability, Statistics, and ScienceReality, Nature, Science, and ModelsStatistical Processes: Nature, Design and Measurement, and DataModelsDeterministic ModelsVariabilityParametersPurely Probabilistic Statistical ModelsStatistical Models with Both Deterministic and Probabilistic ComponentsStatistical InferenceGood and Bad ModelsUses of Probability ModelsRandom Variables and Their Probability DistributionsIntroductionTypes of Random Variables: Nominal, Ordinal, and ContinuousDiscrete Probability Distribution FunctionsContinuous Probability Distribution FunctionsSome Calculus-Derivatives and Least SquaresMore Calculus-Integrals and Cumulative Distribution FunctionsProbability Calculation and SimulationIntroductionAnalytic Calculations, Discrete and Continuous CasesSimulation-Based ApproximationGenerating Random NumbersIdentifying DistributionsIntroductionIdentifying Distributions from Theory AloneUsing Data: Estimating Distributions via the HistogramQuantiles: Theoretical and Data-Based Estimate...

  5. Cancer Statistics

    Science.gov (United States)

    ... What Is Cancer? Cancer Statistics Cancer Disparities Cancer Statistics Cancer has a major impact on society in ... success of efforts to control and manage cancer. Statistics at a Glance: The Burden of Cancer in ...

  6. A statistical-dynamical scheme for reconstructing ocean forcing in the Atlantic. Part I: weather regimes as predictors for ocean surface variables

    Energy Technology Data Exchange (ETDEWEB)

    Cassou, Christophe; Minvielle, Marie; Terray, Laurent [CERFACS/CNRS, Climate Modelling and Global Change Team, Toulouse (France); Perigaud, Claire [JPL-NASA, Ocean Science Element, Pasadena, CA (United States)

    2011-01-15

    The links between the observed variability of the surface ocean variables estimated from reanalysis and the overlying atmosphere decomposed in classes of large-scale atmospheric circulation via clustering are investigated over the Atlantic from 1958 to 2002. Daily 500 hPa geopotential height and 1,000 hPa wind anomaly maps are classified following a weather-typing approach to describe the North Atlantic and tropical Atlantic atmospheric dynamics, respectively. The algorithm yields patterns that correspond in the extratropics to the well-known North Atlantic-Europe weather regimes (NAE-WR) accounting for the barotropic dynamics, and in the tropics to wind classes (T-WC) representing the alteration of the trades. 10-m wind and 2-m temperature (T2) anomaly composites derived from regime/wind class occurrence are indicative of strong relationships between daily large-scale atmospheric circulation and ocean surface over the entire Atlantic basin. High temporal correlation values are obtained basin-wide at low frequency between the observed fields and their reconstruction by multiple linear regressions with the frequencies of occurrence of both NAE-WR and T-WC used as sole predictors. Additional multiple linear regressions also emphasize the importance of accounting for the strength of the daily anomalous atmospheric circulation estimated by the combined distances to all regimes centroids in order to reproduce the daily to interannual variability of the Atlantic ocean. We show that for most of the North Atlantic basin the occurrence of NAE-WR generally sets the sign of the ocean surface anomaly for a given day, and that the inter-regime distances are valuable predictors for the magnitude of that anomaly. Finally, we provide evidence that a large fraction of the low-frequency trends in the Atlantic observed at the surface over the last 50 years can be traced back, except for T2, to changes in occurrence of tropical and extratropical weather classes. All together, our

  7. Dealing with randomness and vagueness in business and management sciences: the fuzzy-probabilistic approach as a tool for the study of statistical relationships between imprecise variables

    Directory of Open Access Journals (Sweden)

    Fabrizio Maturo

    2016-06-01

    Full Text Available In practical applications relating to business and management sciences, there are many variables that, for their own nature, are better described by a pair of ordered values (i.e. financial data. By summarizing this measurement with a single value, there is a loss of information; thus, in these situations, data are better described by interval values rather than by single values. Interval arithmetic studies and analyzes this type of imprecision; however, if the intervals has no sharp boundaries, fuzzy set theory is the most suitable instrument. Moreover, fuzzy regression models are able to overcome some typical limitation of classical regression because they do not need the same strong assumptions. In this paper, we present a review of the main methods introduced in the literature on this topic and introduce some recent developments regarding the concept of randomness in fuzzy regression.

  8. Statistics in a nutshell

    CERN Document Server

    Boslaugh, Sarah

    2013-01-01

    Need to learn statistics for your job? Want help passing a statistics course? Statistics in a Nutshell is a clear and concise introduction and reference for anyone new to the subject. Thoroughly revised and expanded, this edition helps you gain a solid understanding of statistics without the numbing complexity of many college texts. Each chapter presents easy-to-follow descriptions, along with graphics, formulas, solved examples, and hands-on exercises. If you want to perform common statistical analyses and learn a wide range of techniques without getting in over your head, this is your book.

  9. Statistical analysis aiming at predicting respiratory tract disease hospital admissions from environmental variables in the city of São Paulo.

    Science.gov (United States)

    de Sousa Zanotti Stagliorio Coêlho, Micheline; Luiz Teixeira Gonçalves, Fabio; do Rosário Dias de Oliveira Latorre, Maria

    2010-01-01

    This study is aimed at creating a stochastic model, named Brazilian Climate and Health Model (BCHM), through Poisson regression, in order to predict the occurrence of hospital respiratory admissions (for children under thirteen years of age) as a function of air pollutants, meteorological variables, and thermal comfort indices (effective temperatures, ET). The data used in this study were obtained from the city of São Paulo, Brazil, between 1997 and 2000. The respiratory tract diseases were divided into three categories: URI (Upper Respiratory tract diseases), LRI (Lower Respiratory tract diseases), and IP (Influenza and Pneumonia). The overall results of URI, LRI, and IP show clear correlation with SO₂ and CO, PM₁₀ and O₃, and PM₁₀, respectively, and the ETw4 (Effective Temperature) for all the three disease groups. It is extremely important to warn the government of the most populated city in Brazil about the outcome of this study, providing it with valuable information in order to help it better manage its resources on behalf of the whole population of the city of Sao Paulo, especially those with low incomes.

  10. Gum ghatti mediated, one pot green synthesis of optimized gold nanoparticles: Investigation of process-variables impact using Box-Behnken based statistical design.

    Science.gov (United States)

    Alam, Md Sabir; Garg, Arun; Pottoo, Faheem Hyder; Saifullah, Mohammad Khalid; Tareq, Abu Izneid; Manzoor, Ovais; Mohsin, Mohd; Javed, Md Noushad

    2017-11-01

    Due to unique inherent catalytic characteristics of different size, shape and surface functionalized gold nanoparticles, their potential applications, are being explored in various fields such as drug delivery, biosensor, diagnosis and theranostics. However conventional process for synthesis of these metallic nanoparticles utilizes toxic reagents as reducing agents, additional capping agent for stability as well as surface functionalization for drug delivery purposes. Hence, in this work suitability of gum Ghatti for reducing, capping and surface functionalization during the synthesis of stable Gold nanoparticles were duly explored. Role and impact of key process variables i.e. volume of chloroauric acid solution, gum solution and temperature at their respective three different levels, as well as mechanism of formation of optimized gold nanoparticles were also investigated using Box- Behnken design. These novel synthesized optimized Gold nanoparticles were further characterized by UV spectrophotometer for its surface plasmon resonance (SPR) at around ∼530nm, dynamic light scattering (DLS) for its hydrodynamic size (112.5nm), PDI (0.222) and zeta potential (-21.3mV) while, transmission electron microscopy (TEM) further revealed surface geometry of these nanoparticles being spherical in shape. Copyright © 2017 Elsevier B.V. All rights reserved.

  11. Computational statistics handbook with Matlab

    CERN Document Server

    Martinez, Wendy L

    2007-01-01

    Prefaces Introduction What Is Computational Statistics? An Overview of the Book Probability Concepts Introduction Probability Conditional Probability and Independence Expectation Common Distributions Sampling Concepts Introduction Sampling Terminology and Concepts Sampling Distributions Parameter Estimation Empirical Distribution Function Generating Random Variables Introduction General Techniques for Generating Random Variables Generating Continuous Random Variables Generating Discrete Random Variables Exploratory Data Analysis Introduction Exploring Univariate Data Exploring Bivariate and Trivariate Data Exploring Multidimensional Data Finding Structure Introduction Projecting Data Principal Component Analysis Projection Pursuit EDA Independent Component Analysis Grand Tour Nonlinear Dimensionality Reduction Monte Carlo Methods for Inferential Statistics Introduction Classical Inferential Statistics Monte Carlo Methods for Inferential Statist...

  12. Statistics 101 for Radiologists.

    Science.gov (United States)

    Anvari, Arash; Halpern, Elkan F; Samir, Anthony E

    2015-10-01

    Diagnostic tests have wide clinical applications, including screening, diagnosis, measuring treatment effect, and determining prognosis. Interpreting diagnostic test results requires an understanding of key statistical concepts used to evaluate test efficacy. This review explains descriptive statistics and discusses probability, including mutually exclusive and independent events and conditional probability. In the inferential statistics section, a statistical perspective on study design is provided, together with an explanation of how to select appropriate statistical tests. Key concepts in recruiting study samples are discussed, including representativeness and random sampling. Variable types are defined, including predictor, outcome, and covariate variables, and the relationship of these variables to one another. In the hypothesis testing section, we explain how to determine if observed differences between groups are likely to be due to chance. We explain type I and II errors, statistical significance, and study power, followed by an explanation of effect sizes and how confidence intervals can be used to generalize observed effect sizes to the larger population. Statistical tests are explained in four categories: t tests and analysis of variance, proportion analysis tests, nonparametric tests, and regression techniques. We discuss sensitivity, specificity, accuracy, receiver operating characteristic analysis, and likelihood ratios. Measures of reliability and agreement, including κ statistics, intraclass correlation coefficients, and Bland-Altman graphs and analysis, are introduced. © RSNA, 2015.

  13. Introduction to Bayesian statistics

    CERN Document Server

    Bolstad, William M

    2017-01-01

    There is a strong upsurge in the use of Bayesian methods in applied statistical analysis, yet most introductory statistics texts only present frequentist methods. Bayesian statistics has many important advantages that students should learn about if they are going into fields where statistics will be used. In this Third Edition, four newly-added chapters address topics that reflect the rapid advances in the field of Bayesian staistics. The author continues to provide a Bayesian treatment of introductory statistical topics, such as scientific data gathering, discrete random variables, robust Bayesian methods, and Bayesian approaches to inferenfe cfor discrete random variables, bionomial proprotion, Poisson, normal mean, and simple linear regression. In addition, newly-developing topics in the field are presented in four new chapters: Bayesian inference with unknown mean and variance; Bayesian inference for Multivariate Normal mean vector; Bayesian inference for Multiple Linear RegressionModel; and Computati...

  14. A controlled statistical study to assess measurement variability as a function of test object position and configuration for automated surveillance in a multicenter longitudinal COPD study (SPIROMICS)

    International Nuclear Information System (INIS)

    Guo, Junfeng; Newell, John D.; Wang, Chao; Chan, Kung-Sik; Jin, Dakai; Saha, Punam K.; Sieren, Jered P.; Barr, R. G.; Han, MeiLan K.; Kazerooni, Ella; Cooper, Christopher B.; Couper, David; Hoffman, Eric A.

    2016-01-01

    Purpose: A test object (phantom) is an important tool to evaluate comparability and stability of CT scanners used in multicenter and longitudinal studies. However, there are many sources of error that can interfere with the test object-derived quantitative measurements. Here the authors investigated three major possible sources of operator error in the use of a test object employed to assess pulmonary density-related as well as airway-related metrics. Methods: Two kinds of experiments were carried out to assess measurement variability caused by imperfect scanning status. The first one consisted of three experiments. A COPDGene test object was scanned using a dual source multidetector computed tomographic scanner (Siemens Somatom Flash) with the Subpopulations and Intermediate Outcome Measures in COPD Study (SPIROMICS) inspiration protocol (120 kV, 110 mAs, pitch = 1, slice thickness = 0.75 mm, slice spacing = 0.5 mm) to evaluate the effects of tilt angle, water bottle offset, and air bubble size. After analysis of these results, a guideline was reached in order to achieve more reliable results for this test object. Next the authors applied the above findings to 2272 test object scans collected over 4 years as part of the SPIROMICS study. The authors compared changes of the data consistency before and after excluding the scans that failed to pass the guideline. Results: This study established the following limits for the test object: tilt index ≤0.3, water bottle offset limits of [−6.6 mm, 7.4 mm], and no air bubble within the water bottle, where tilt index is a measure incorporating two tilt angles around x- and y-axis. With 95% confidence, the density measurement variation for all five interested materials in the test object (acrylic, water, lung, inside air, and outside air) resulting from all three error sources can be limited to ±0.9 HU (summed in quadrature), when all the requirements are satisfied. The authors applied these criteria to 2272 SPIROMICS

  15. A controlled statistical study to assess measurement variability as a function of test object position and configuration for automated surveillance in a multicenter longitudinal COPD study (SPIROMICS)

    Energy Technology Data Exchange (ETDEWEB)

    Guo, Junfeng; Newell, John D. [Departments of Radiology and Biomedical Engineering, University of Iowa, Iowa City, Iowa 52242 (United States); Wang, Chao; Chan, Kung-Sik [Department of Statistics and Actuarial Science, University of Iowa, Iowa City, Iowa 52242 (United States); Jin, Dakai; Saha, Punam K. [Department of Electrical and Computer Engineering, University of Iowa, Iowa City, Iowa 52242 (United States); Sieren, Jered P. [Department of Radiology, University of Iowa, Iowa City, Iowa 52242 (United States); Barr, R. G. [Departments of Medicine and Epidemiology, Columbia University Medical Center, New York, New York 10032 (United States); Han, MeiLan K. [Department of Medicine, Division of Pulmonary and Critical Care Medicine, University of Michigan, Ann Arbor, Michigan 48109 (United States); Kazerooni, Ella [Department of Radiology, University of Michigan, Ann Arbor, Michigan 48109 (United States); Cooper, Christopher B. [Department of Medicine, University of California, Los Angeles, California 90095 (United States); Couper, David [Department of Biostatistics, University of North Carolina, Chapel Hill, North Carolina 27599 (United States); Hoffman, Eric A., E-mail: eric-hoffman@uiowa.edu [Departments of Radiology, Medicine and Biomedical Engineering, University of Iowa, Iowa City, Iowa 52242 (United States)

    2016-05-15

    Purpose: A test object (phantom) is an important tool to evaluate comparability and stability of CT scanners used in multicenter and longitudinal studies. However, there are many sources of error that can interfere with the test object-derived quantitative measurements. Here the authors investigated three major possible sources of operator error in the use of a test object employed to assess pulmonary density-related as well as airway-related metrics. Methods: Two kinds of experiments were carried out to assess measurement variability caused by imperfect scanning status. The first one consisted of three experiments. A COPDGene test object was scanned using a dual source multidetector computed tomographic scanner (Siemens Somatom Flash) with the Subpopulations and Intermediate Outcome Measures in COPD Study (SPIROMICS) inspiration protocol (120 kV, 110 mAs, pitch = 1, slice thickness = 0.75 mm, slice spacing = 0.5 mm) to evaluate the effects of tilt angle, water bottle offset, and air bubble size. After analysis of these results, a guideline was reached in order to achieve more reliable results for this test object. Next the authors applied the above findings to 2272 test object scans collected over 4 years as part of the SPIROMICS study. The authors compared changes of the data consistency before and after excluding the scans that failed to pass the guideline. Results: This study established the following limits for the test object: tilt index ≤0.3, water bottle offset limits of [−6.6 mm, 7.4 mm], and no air bubble within the water bottle, where tilt index is a measure incorporating two tilt angles around x- and y-axis. With 95% confidence, the density measurement variation for all five interested materials in the test object (acrylic, water, lung, inside air, and outside air) resulting from all three error sources can be limited to ±0.9 HU (summed in quadrature), when all the requirements are satisfied. The authors applied these criteria to 2272 SPIROMICS

  16. Sensitivity and uncertainty analyses for performance assessment modeling

    International Nuclear Information System (INIS)

    Doctor, P.G.

    1988-08-01

    Sensitivity and uncertainty analyses methods for computer models are being applied in performance assessment modeling in the geologic high level radioactive waste repository program. The models used in performance assessment tend to be complex physical/chemical models with large numbers of input variables. There are two basic approaches to sensitivity and uncertainty analyses: deterministic and statistical. The deterministic approach to sensitivity analysis involves numerical calculation or employs the adjoint form of a partial differential equation to compute partial derivatives; the uncertainty analysis is based on Taylor series expansions of the input variables propagated through the model to compute means and variances of the output variable. The statistical approach to sensitivity analysis involves a response surface approximation to the model with the sensitivity coefficients calculated from the response surface parameters; the uncertainty analysis is based on simulation. The methods each have strengths and weaknesses. 44 refs

  17. Usage Statistics

    Science.gov (United States)

    ... this page: https://medlineplus.gov/usestatistics.html MedlinePlus Statistics To use the sharing features on this page, ... By Quarter View image full size Quarterly User Statistics Quarter Page Views Unique Visitors Oct-Dec-98 ...

  18. Mathematical statistics

    CERN Document Server

    Pestman, Wiebe R

    2009-01-01

    This textbook provides a broad and solid introduction to mathematical statistics, including the classical subjects hypothesis testing, normal regression analysis, and normal analysis of variance. In addition, non-parametric statistics and vectorial statistics are considered, as well as applications of stochastic analysis in modern statistics, e.g., Kolmogorov-Smirnov testing, smoothing techniques, robustness and density estimation. For students with some elementary mathematical background. With many exercises. Prerequisites from measure theory and linear algebra are presented.

  19. Frog Statistics

    Science.gov (United States)

    Whole Frog Project and Virtual Frog Dissection Statistics wwwstats output for January 1 through duplicate or extraneous accesses. For example, in these statistics, while a POST requesting an image is as well. Note that this under-represents the bytes requested. Starting date for following statistics

  20. The statistical stability phenomenon

    CERN Document Server

    Gorban, Igor I

    2017-01-01

    This monograph investigates violations of statistical stability of physical events, variables, and processes and develops a new physical-mathematical theory taking into consideration such violations – the theory of hyper-random phenomena. There are five parts. The first describes the phenomenon of statistical stability and its features, and develops methods for detecting violations of statistical stability, in particular when data is limited. The second part presents several examples of real processes of different physical nature and demonstrates the violation of statistical stability over broad observation intervals. The third part outlines the mathematical foundations of the theory of hyper-random phenomena, while the fourth develops the foundations of the mathematical analysis of divergent and many-valued functions. The fifth part contains theoretical and experimental studies of statistical laws where there is violation of statistical stability. The monograph should be of particular interest to engineers...

  1. Statistical physics

    CERN Document Server

    Sadovskii, Michael V

    2012-01-01

    This volume provides a compact presentation of modern statistical physics at an advanced level. Beginning with questions on the foundations of statistical mechanics all important aspects of statistical physics are included, such as applications to ideal gases, the theory of quantum liquids and superconductivity and the modern theory of critical phenomena. Beyond that attention is given to new approaches, such as quantum field theory methods and non-equilibrium problems.

  2. STATISTICAL OPTIMIZATION OF PROCESS VARIABLES FOR ...

    African Journals Online (AJOL)

    2012-11-03

    Nov 3, 2012 ... The osmotic dehydration process was optimized for water loss and solutes gain. ... basis) with safe moisture content for storage (10% wet basis) [3]. Due to ... sucrose, glucose, fructose, corn syrup and sodium chlo- ride have ...

  3. Statistical optics

    CERN Document Server

    Goodman, Joseph W

    2015-01-01

    This book discusses statistical methods that are useful for treating problems in modern optics, and the application of these methods to solving a variety of such problems This book covers a variety of statistical problems in optics, including both theory and applications.  The text covers the necessary background in statistics, statistical properties of light waves of various types, the theory of partial coherence and its applications, imaging with partially coherent light, atmospheric degradations of images, and noise limitations in the detection of light. New topics have been introduced i

  4. Harmonic statistics

    Energy Technology Data Exchange (ETDEWEB)

    Eliazar, Iddo, E-mail: eliazar@post.tau.ac.il

    2017-05-15

    The exponential, the normal, and the Poisson statistical laws are of major importance due to their universality. Harmonic statistics are as universal as the three aforementioned laws, but yet they fall short in their ‘public relations’ for the following reason: the full scope of harmonic statistics cannot be described in terms of a statistical law. In this paper we describe harmonic statistics, in their full scope, via an object termed harmonic Poisson process: a Poisson process, over the positive half-line, with a harmonic intensity. The paper reviews the harmonic Poisson process, investigates its properties, and presents the connections of this object to an assortment of topics: uniform statistics, scale invariance, random multiplicative perturbations, Pareto and inverse-Pareto statistics, exponential growth and exponential decay, power-law renormalization, convergence and domains of attraction, the Langevin equation, diffusions, Benford’s law, and 1/f noise. - Highlights: • Harmonic statistics are described and reviewed in detail. • Connections to various statistical laws are established. • Connections to perturbation, renormalization and dynamics are established.

  5. Harmonic statistics

    International Nuclear Information System (INIS)

    Eliazar, Iddo

    2017-01-01

    The exponential, the normal, and the Poisson statistical laws are of major importance due to their universality. Harmonic statistics are as universal as the three aforementioned laws, but yet they fall short in their ‘public relations’ for the following reason: the full scope of harmonic statistics cannot be described in terms of a statistical law. In this paper we describe harmonic statistics, in their full scope, via an object termed harmonic Poisson process: a Poisson process, over the positive half-line, with a harmonic intensity. The paper reviews the harmonic Poisson process, investigates its properties, and presents the connections of this object to an assortment of topics: uniform statistics, scale invariance, random multiplicative perturbations, Pareto and inverse-Pareto statistics, exponential growth and exponential decay, power-law renormalization, convergence and domains of attraction, the Langevin equation, diffusions, Benford’s law, and 1/f noise. - Highlights: • Harmonic statistics are described and reviewed in detail. • Connections to various statistical laws are established. • Connections to perturbation, renormalization and dynamics are established.

  6. Statistical methods

    CERN Document Server

    Szulc, Stefan

    1965-01-01

    Statistical Methods provides a discussion of the principles of the organization and technique of research, with emphasis on its application to the problems in social statistics. This book discusses branch statistics, which aims to develop practical ways of collecting and processing numerical data and to adapt general statistical methods to the objectives in a given field.Organized into five parts encompassing 22 chapters, this book begins with an overview of how to organize the collection of such information on individual units, primarily as accomplished by government agencies. This text then

  7. Histoplasmosis Statistics

    Science.gov (United States)

    ... Testing Treatment & Outcomes Health Professionals Statistics More Resources Candidiasis Candida infections of the mouth, throat, and esophagus Vaginal candidiasis Invasive candidiasis Definition Symptoms Risk & Prevention Sources Diagnosis ...

  8. Biological variability of glycated hemoglobin.

    Science.gov (United States)

    Braga, Federica; Dolci, Alberto; Mosca, Andrea; Panteghini, Mauro

    2010-11-11

    The measurement of glycated hemoglobin (HbA(1c)) has a pivotal role in monitoring glycemic state in diabetic patients. Furthermore, the American Diabetes Association has recently recommended the use of HbA(1c) for diabetes diagnosis, but a clear definition of the clinically allowable measurement error is still lacking. Information on biological variability of the analyte can be used to achieve this goal. We systematically reviewed the published studies on the biological variation of HbA(1c) to check consistency of available data in order to accurately define analytical goals. The nine recruited studies were limited by choice of analytic methodology, population selection, protocol application and statistical analyses. There is an urgent need to determine biological variability of HbA(1c) using a specific and traceable assay, appropriate protocol and appropriate statistical evaluation of data. 2010 Elsevier B.V. All rights reserved.

  9. Introductory statistical inference

    CERN Document Server

    Mukhopadhyay, Nitis

    2014-01-01

    This gracefully organized text reveals the rigorous theory of probability and statistical inference in the style of a tutorial, using worked examples, exercises, figures, tables, and computer simulations to develop and illustrate concepts. Drills and boxed summaries emphasize and reinforce important ideas and special techniques.Beginning with a review of the basic concepts and methods in probability theory, moments, and moment generating functions, the author moves to more intricate topics. Introductory Statistical Inference studies multivariate random variables, exponential families of dist

  10. Multivariate statistical methods and data mining in particle physics (4/4)

    CERN Multimedia

    CERN. Geneva

    2008-01-01

    The lectures will cover multivariate statistical methods and their applications in High Energy Physics. The methods will be viewed in the framework of a statistical test, as used e.g. to discriminate between signal and background events. Topics will include an introduction to the relevant statistical formalism, linear test variables, neural networks, probability density estimation (PDE) methods, kernel-based PDE, decision trees and support vector machines. The methods will be evaluated with respect to criteria relevant to HEP analyses such as statistical power, ease of computation and sensitivity to systematic effects. Simple computer examples that can be extended to more complex analyses will be presented.

  11. Multivariate statistical methods and data mining in particle physics (2/4)

    CERN Multimedia

    CERN. Geneva

    2008-01-01

    The lectures will cover multivariate statistical methods and their applications in High Energy Physics. The methods will be viewed in the framework of a statistical test, as used e.g. to discriminate between signal and background events. Topics will include an introduction to the relevant statistical formalism, linear test variables, neural networks, probability density estimation (PDE) methods, kernel-based PDE, decision trees and support vector machines. The methods will be evaluated with respect to criteria relevant to HEP analyses such as statistical power, ease of computation and sensitivity to systematic effects. Simple computer examples that can be extended to more complex analyses will be presented.

  12. Multivariate statistical methods and data mining in particle physics (1/4)

    CERN Multimedia

    CERN. Geneva

    2008-01-01

    The lectures will cover multivariate statistical methods and their applications in High Energy Physics. The methods will be viewed in the framework of a statistical test, as used e.g. to discriminate between signal and background events. Topics will include an introduction to the relevant statistical formalism, linear test variables, neural networks, probability density estimation (PDE) methods, kernel-based PDE, decision trees and support vector machines. The methods will be evaluated with respect to criteria relevant to HEP analyses such as statistical power, ease of computation and sensitivity to systematic effects. Simple computer examples that can be extended to more complex analyses will be presented.

  13. Statistical Diversions

    Science.gov (United States)

    Petocz, Peter; Sowey, Eric

    2008-01-01

    In this article, the authors focus on hypothesis testing--that peculiarly statistical way of deciding things. Statistical methods for testing hypotheses were developed in the 1920s and 1930s by some of the most famous statisticians, in particular Ronald Fisher, Jerzy Neyman and Egon Pearson, who laid the foundations of almost all modern methods of…

  14. Scan Statistics

    CERN Document Server

    Glaz, Joseph

    2009-01-01

    Suitable for graduate students and researchers in applied probability and statistics, as well as for scientists in biology, computer science, pharmaceutical science and medicine, this title brings together a collection of chapters illustrating the depth and diversity of theory, methods and applications in the area of scan statistics.

  15. Lehrer in der Bundesrepublik Deutschland. Eine Kritische Analyse Statistischer Daten uber das Lehrpersonal an Allgemeinbildenden Schulen. (Education in the Federal Republic of Germany. A Statistical Study of Teachers in Schools of General Education.)

    Science.gov (United States)

    Kohler, Helmut

    The purpose of this study was to analyze the available statistics concerning teachers in schools of general education in the Federal Republic of Germany. An analysis of the demographic structure of the pool of full-time teachers showed that in 1971 30 percent of the teachers were under age 30, and 50 percent were under age 35. It was expected that…

  16. A Multi-Faceted Approach to Analyse the Effects of Environmental Variables on Geographic Range and Genetic Structure of a Perennial Psammophilous Geophyte: The Case of the Sea Daffodil Pancratium maritimum L. in the Mediterranean Basin.

    Directory of Open Access Journals (Sweden)

    Olga De Castro

    Full Text Available The Mediterranean coastline is a dynamic and complex system which owes its complexity to its past and present vicissitudes, e.g. complex tectonic history, climatic fluctuations, and prolonged coexistence with human activities. A plant species that is widespread in this habitat is the sea daffodil, Pancratium maritimum (Amaryllidaceae, which is a perennial clonal geophyte of the coastal sands of the Mediterranean and neighbouring areas, well adapted to the stressful conditions of sand dune environments. In this study, an integrated approach was used, combining genetic and environmental data with a niche modelling approach, aimed to investigate: (1 the effect of climate change on the geographic range of this species at different times {past (last inter-glacial, LIG; and last glacial maximum, LGM, present (CURR, near-future (FUT} and (2 the possible influence of environmental variables on the genetic structure of this species in the current period. The genetic results show that 48 sea daffodil populations (867 specimens display a good genetic diversity in which the marginal populations (i.e. Atlantic Sea populations present lower values. Recent genetic signature of bottleneck was detected in few populations (8%. The molecular variation was higher within the populations (77% and two genetic pools were well represented. Comparing the different climatic simulations in time, the global range of this plant increased, and a further extension is foreseen in the near future thanks to projections on the climate of areas currently-more temperate, where our model suggested a forecast for a climate more similar to the Mediterranean coast. A significant positive correlation was observed between the genetic distance and Precipitation of Coldest Quarter variable in current periods. Our analyses support the hypothesis that geomorphology of the Mediterranean coasts, sea currents, and climate have played significant roles in shaping the current genetic structure of

  17. A Multi-Faceted Approach to Analyse the Effects of Environmental Variables on Geographic Range and Genetic Structure of a Perennial Psammophilous Geophyte: The Case of the Sea Daffodil Pancratium maritimum L. in the Mediterranean Basin.

    Science.gov (United States)

    De Castro, Olga; Di Maio, Antonietta; Di Febbraro, Mirko; Imparato, Gennaro; Innangi, Michele; Véla, Errol; Menale, Bruno

    2016-01-01

    The Mediterranean coastline is a dynamic and complex system which owes its complexity to its past and present vicissitudes, e.g. complex tectonic history, climatic fluctuations, and prolonged coexistence with human activities. A plant species that is widespread in this habitat is the sea daffodil, Pancratium maritimum (Amaryllidaceae), which is a perennial clonal geophyte of the coastal sands of the Mediterranean and neighbouring areas, well adapted to the stressful conditions of sand dune environments. In this study, an integrated approach was used, combining genetic and environmental data with a niche modelling approach, aimed to investigate: (1) the effect of climate change on the geographic range of this species at different times {past (last inter-glacial, LIG; and last glacial maximum, LGM), present (CURR), near-future (FUT)} and (2) the possible influence of environmental variables on the genetic structure of this species in the current period. The genetic results show that 48 sea daffodil populations (867 specimens) display a good genetic diversity in which the marginal populations (i.e. Atlantic Sea populations) present lower values. Recent genetic signature of bottleneck was detected in few populations (8%). The molecular variation was higher within the populations (77%) and two genetic pools were well represented. Comparing the different climatic simulations in time, the global range of this plant increased, and a further extension is foreseen in the near future thanks to projections on the climate of areas currently-more temperate, where our model suggested a forecast for a climate more similar to the Mediterranean coast. A significant positive correlation was observed between the genetic distance and Precipitation of Coldest Quarter variable in current periods. Our analyses support the hypothesis that geomorphology of the Mediterranean coasts, sea currents, and climate have played significant roles in shaping the current genetic structure of the sea

  18. A canonical neural mechanism for behavioral variability

    Science.gov (United States)

    Darshan, Ran; Wood, William E.; Peters, Susan; Leblois, Arthur; Hansel, David

    2017-05-01

    The ability to generate variable movements is essential for learning and adjusting complex behaviours. This variability has been linked to the temporal irregularity of neuronal activity in the central nervous system. However, how neuronal irregularity actually translates into behavioural variability is unclear. Here we combine modelling, electrophysiological and behavioural studies to address this issue. We demonstrate that a model circuit comprising topographically organized and strongly recurrent neural networks can autonomously generate irregular motor behaviours. Simultaneous recordings of neurons in singing finches reveal that neural correlations increase across the circuit driving song variability, in agreement with the model predictions. Analysing behavioural data, we find remarkable similarities in the babbling statistics of 5-6-month-old human infants and juveniles from three songbird species and show that our model naturally accounts for these `universal' statistics.

  19. Mathematical statistics and stochastic processes

    CERN Document Server

    Bosq, Denis

    2013-01-01

    Generally, books on mathematical statistics are restricted to the case of independent identically distributed random variables. In this book however, both this case AND the case of dependent variables, i.e. statistics for discrete and continuous time processes, are studied. This second case is very important for today's practitioners.Mathematical Statistics and Stochastic Processes is based on decision theory and asymptotic statistics and contains up-to-date information on the relevant topics of theory of probability, estimation, confidence intervals, non-parametric statistics and rob

  20. Statistical Analysis of Data for Timber Strengths

    DEFF Research Database (Denmark)

    Sørensen, John Dalsgaard; Hoffmeyer, P.

    Statistical analyses are performed for material strength parameters from approximately 6700 specimens of structural timber. Non-parametric statistical analyses and fits to the following distributions types have been investigated: Normal, Lognormal, 2 parameter Weibull and 3-parameter Weibull...

  1. Semiconductor statistics

    CERN Document Server

    Blakemore, J S

    1962-01-01

    Semiconductor Statistics presents statistics aimed at complementing existing books on the relationships between carrier densities and transport effects. The book is divided into two parts. Part I provides introductory material on the electron theory of solids, and then discusses carrier statistics for semiconductors in thermal equilibrium. Of course a solid cannot be in true thermodynamic equilibrium if any electrical current is passed; but when currents are reasonably small the distribution function is but little perturbed, and the carrier distribution for such a """"quasi-equilibrium"""" co

  2. Statistical Physics

    CERN Document Server

    Wannier, Gregory Hugh

    1966-01-01

    Until recently, the field of statistical physics was traditionally taught as three separate subjects: thermodynamics, statistical mechanics, and kinetic theory. This text, a forerunner in its field and now a classic, was the first to recognize the outdated reasons for their separation and to combine the essentials of the three subjects into one unified presentation of thermal physics. It has been widely adopted in graduate and advanced undergraduate courses, and is recommended throughout the field as an indispensable aid to the independent study and research of statistical physics.Designed for

  3. Statistical Pattern Recognition

    CERN Document Server

    Webb, Andrew R

    2011-01-01

    Statistical pattern recognition relates to the use of statistical techniques for analysing data measurements in order to extract information and make justified decisions.  It is a very active area of study and research, which has seen many advances in recent years. Applications such as data mining, web searching, multimedia data retrieval, face recognition, and cursive handwriting recognition, all require robust and efficient pattern recognition techniques. This third edition provides an introduction to statistical pattern theory and techniques, with material drawn from a wide range of fields,

  4. Basic statistical tools in research and data analysis

    Directory of Open Access Journals (Sweden)

    Zulfiqar Ali

    2016-01-01

    Full Text Available Statistical methods involved in carrying out a study include planning, designing, collecting data, analysing, drawing meaningful interpretation and reporting of the research findings. The statistical analysis gives meaning to the meaningless numbers, thereby breathing life into a lifeless data. The results and inferences are precise only if proper statistical tests are used. This article will try to acquaint the reader with the basic research tools that are utilised while conducting various studies. The article covers a brief outline of the variables, an understanding of quantitative and qualitative variables and the measures of central tendency. An idea of the sample size estimation, power analysis and the statistical errors is given. Finally, there is a summary of parametric and non-parametric tests used for data analysis.

  5. Image Statistics

    Energy Technology Data Exchange (ETDEWEB)

    Wendelberger, Laura Jean [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2017-08-08

    In large datasets, it is time consuming or even impossible to pick out interesting images. Our proposed solution is to find statistics to quantify the information in each image and use those to identify and pick out images of interest.

  6. CMS Statistics

    Data.gov (United States)

    U.S. Department of Health & Human Services — The CMS Center for Strategic Planning produces an annual CMS Statistics reference booklet that provides a quick reference for summary information about health...

  7. WPRDC Statistics

    Data.gov (United States)

    Allegheny County / City of Pittsburgh / Western PA Regional Data Center — Data about the usage of the WPRDC site and its various datasets, obtained by combining Google Analytics statistics with information from the WPRDC's data portal.

  8. Multiparametric statistics

    CERN Document Server

    Serdobolskii, Vadim Ivanovich

    2007-01-01

    This monograph presents mathematical theory of statistical models described by the essentially large number of unknown parameters, comparable with sample size but can also be much larger. In this meaning, the proposed theory can be called "essentially multiparametric". It is developed on the basis of the Kolmogorov asymptotic approach in which sample size increases along with the number of unknown parameters.This theory opens a way for solution of central problems of multivariate statistics, which up until now have not been solved. Traditional statistical methods based on the idea of an infinite sampling often break down in the solution of real problems, and, dependent on data, can be inefficient, unstable and even not applicable. In this situation, practical statisticians are forced to use various heuristic methods in the hope the will find a satisfactory solution.Mathematical theory developed in this book presents a regular technique for implementing new, more efficient versions of statistical procedures. ...

  9. Gonorrhea Statistics

    Science.gov (United States)

    ... Search Form Controls Cancel Submit Search the CDC Gonorrhea Note: Javascript is disabled or is not supported ... Twitter STD on Facebook Sexually Transmitted Diseases (STDs) Gonorrhea Statistics Recommend on Facebook Tweet Share Compartir Gonorrhea ...

  10. Reversible Statistics

    DEFF Research Database (Denmark)

    Tryggestad, Kjell

    2004-01-01

    The study aims is to describe how the inclusion and exclusion of materials and calculative devices construct the boundaries and distinctions between statistical facts and artifacts in economics. My methodological approach is inspired by John Graunt's (1667) Political arithmetic and more recent work...... within constructivism and the field of Science and Technology Studies (STS). The result of this approach is here termed reversible statistics, reconstructing the findings of a statistical study within economics in three different ways. It is argued that all three accounts are quite normal, albeit...... in different ways. The presence and absence of diverse materials, both natural and political, is what distinguishes them from each other. Arguments are presented for a more symmetric relation between the scientific statistical text and the reader. I will argue that a more symmetric relation can be achieved...

  11. Notices about using elementary statistics in psychology

    OpenAIRE

    松田, 文子; 三宅, 幹子; 橋本, 優花里; 山崎, 理央; 森田, 愛子; 小嶋, 佳子

    2003-01-01

    Improper uses of elementary statistics that were often observed in beginners' manuscripts and papers were collected and better ways were suggested. This paper consists of three parts: About descriptive statistics, multivariate analyses, and statistical tests.

  12. Does environmental data collection need statistics?

    NARCIS (Netherlands)

    Pulles, M.P.J.

    1998-01-01

    The term 'statistics' with reference to environmental science and policymaking might mean different things: the development of statistical methodology, the methodology developed by statisticians to interpret and analyse such data, or the statistical data that are needed to understand environmental

  13. Vital statistics

    CERN Document Server

    MacKenzie, Dana

    2004-01-01

    The drawbacks of using 19th-century mathematics in physics and astronomy are illustrated. To continue with the expansion of the knowledge about the cosmos, the scientists will have to come in terms with modern statistics. Some researchers have deliberately started importing techniques that are used in medical research. However, the physicists need to identify the brand of statistics that will be suitable for them, and make a choice between the Bayesian and the frequentists approach. (Edited abstract).

  14. Per Object statistical analysis

    DEFF Research Database (Denmark)

    2008-01-01

    of a specific class in turn, and uses as pair of PPO stages to derive the statistics and then assign them to the objects' Object Variables. It may be that this could all be done in some other, simply way, but several other ways that were tried did not succeed. The procedure ouptut has been tested against...

  15. The Need for Speed in Rodent Locomotion Analyses

    Science.gov (United States)

    Batka, Richard J.; Brown, Todd J.; Mcmillan, Kathryn P.; Meadows, Rena M.; Jones, Kathryn J.; Haulcomb, Melissa M.

    2016-01-01

    Locomotion analysis is now widely used across many animal species to understand the motor defects in disease, functional recovery following neural injury, and the effectiveness of various treatments. More recently, rodent locomotion analysis has become an increasingly popular method in a diverse range of research. Speed is an inseparable aspect of locomotion that is still not fully understood, and its effects are often not properly incorporated while analyzing data. In this hybrid manuscript, we accomplish three things: (1) review the interaction between speed and locomotion variables in rodent studies, (2) comprehensively analyze the relationship between speed and 162 locomotion variables in a group of 16 wild-type mice using the CatWalk gait analysis system, and (3) develop and test a statistical method in which locomotion variables are analyzed and reported in the context of speed. Notable results include the following: (1) over 90% of variables, reported by CatWalk, were dependent on speed with an average R2 value of 0.624, (2) most variables were related to speed in a nonlinear manner, (3) current methods of controlling for speed are insufficient, and (4) the linear mixed model is an appropriate and effective statistical method for locomotion analyses that is inclusive of speed-dependent relationships. Given the pervasive dependency of locomotion variables on speed, we maintain that valid conclusions from locomotion analyses cannot be made unless they are analyzed and reported within the context of speed. PMID:24890845

  16. The Statistical Fermi Paradox

    Science.gov (United States)

    Maccone, C.

    In this paper is provided the statistical generalization of the Fermi paradox. The statistics of habitable planets may be based on a set of ten (and possibly more) astrobiological requirements first pointed out by Stephen H. Dole in his book Habitable planets for man (1964). The statistical generalization of the original and by now too simplistic Dole equation is provided by replacing a product of ten positive numbers by the product of ten positive random variables. This is denoted the SEH, an acronym standing for “Statistical Equation for Habitables”. The proof in this paper is based on the Central Limit Theorem (CLT) of Statistics, stating that the sum of any number of independent random variables, each of which may be ARBITRARILY distributed, approaches a Gaussian (i.e. normal) random variable (Lyapunov form of the CLT). It is then shown that: 1. The new random variable NHab, yielding the number of habitables (i.e. habitable planets) in the Galaxy, follows the log- normal distribution. By construction, the mean value of this log-normal distribution is the total number of habitable planets as given by the statistical Dole equation. 2. The ten (or more) astrobiological factors are now positive random variables. The probability distribution of each random variable may be arbitrary. The CLT in the so-called Lyapunov or Lindeberg forms (that both do not assume the factors to be identically distributed) allows for that. In other words, the CLT "translates" into the SEH by allowing an arbitrary probability distribution for each factor. This is both astrobiologically realistic and useful for any further investigations. 3. By applying the SEH it is shown that the (average) distance between any two nearby habitable planets in the Galaxy may be shown to be inversely proportional to the cubic root of NHab. This distance is denoted by new random variable D. The relevant probability density function is derived, which was named the "Maccone distribution" by Paul Davies in

  17. Statistics for experimentalists

    CERN Document Server

    Cooper, B E

    2014-01-01

    Statistics for Experimentalists aims to provide experimental scientists with a working knowledge of statistical methods and search approaches to the analysis of data. The book first elaborates on probability and continuous probability distributions. Discussions focus on properties of continuous random variables and normal variables, independence of two random variables, central moments of a continuous distribution, prediction from a normal distribution, binomial probabilities, and multiplication of probabilities and independence. The text then examines estimation and tests of significance. Topics include estimators and estimates, expected values, minimum variance linear unbiased estimators, sufficient estimators, methods of maximum likelihood and least squares, and the test of significance method. The manuscript ponders on distribution-free tests, Poisson process and counting problems, correlation and function fitting, balanced incomplete randomized block designs and the analysis of covariance, and experiment...

  18. A statistical evaluation of asbestos air concentrations

    Energy Technology Data Exchange (ETDEWEB)

    Lange, J.H. [Envirosafe Training and Consultants, Pittsburgh, PA (United States)

    1999-07-01

    Both area and personal air samples collected during an asbestos abatement project were matched and statistically analysed. Among the many parameters studied were fibre concentrations and their variability. Mean values for area and personal samples were 0.005 and 0.024 f cm{sup -}-{sup 3} of air, respectively. Summary values for area and personal samples suggest that exposures are low with no single exposure value exceeding the current OSHA TWA value of 0.1 f cm{sup -3} of air. Within- and between-worker analysis suggests that these data are homogeneous. Comparison of within- and between-worker values suggests that the exposure source and variability for abatement are more related to the process than individual practices. This supports the importance of control measures for abatement. Study results also suggest that area and personal samples are not statistically related, that is, there is no association observed for these two sampling methods when data are analysed by correlation or regression analysis. Personal samples were statistically higher in concentration than area samples. Area sampling cannot be used as a surrogate exposure for asbestos abatement workers. (author)

  19. A statistical evaluation of asbestos air concentrations

    International Nuclear Information System (INIS)

    Lange, J.H.

    1999-01-01

    Both area and personal air samples collected during an asbestos abatement project were matched and statistically analysed. Among the many parameters studied were fibre concentrations and their variability. Mean values for area and personal samples were 0.005 and 0.024 f cm - - 3 of air, respectively. Summary values for area and personal samples suggest that exposures are low with no single exposure value exceeding the current OSHA TWA value of 0.1 f cm -3 of air. Within- and between-worker analysis suggests that these data are homogeneous. Comparison of within- and between-worker values suggests that the exposure source and variability for abatement are more related to the process than individual practices. This supports the importance of control measures for abatement. Study results also suggest that area and personal samples are not statistically related, that is, there is no association observed for these two sampling methods when data are analysed by correlation or regression analysis. Personal samples were statistically higher in concentration than area samples. Area sampling cannot be used as a surrogate exposure for asbestos abatement workers. (author)

  20. Implementation of quality by design principles in the development of microsponges as drug delivery carriers: Identification and optimization of critical factors using multivariate statistical analyses and design of experiments studies.

    Science.gov (United States)

    Simonoska Crcarevska, Maja; Dimitrovska, Aneta; Sibinovska, Nadica; Mladenovska, Kristina; Slavevska Raicki, Renata; Glavas Dodov, Marija

    2015-07-15

    Microsponges drug delivery system (MDDC) was prepared by double emulsion-solvent-diffusion technique using rotor-stator homogenization. Quality by design (QbD) concept was implemented for the development of MDDC with potential to be incorporated into semisolid dosage form (gel). Quality target product profile (QTPP) and critical quality attributes (CQA) were defined and identified, accordingly. Critical material attributes (CMA) and Critical process parameters (CPP) were identified using quality risk management (QRM) tool, failure mode, effects and criticality analysis (FMECA). CMA and CPP were identified based on results obtained from principal component analysis (PCA-X&Y) and partial least squares (PLS) statistical analysis along with literature data, product and process knowledge and understanding. FMECA identified amount of ethylcellulose, chitosan, acetone, dichloromethane, span 80, tween 80 and water ratio in primary/multiple emulsions as CMA and rotation speed and stirrer type used for organic solvent removal as CPP. The relationship between identified CPP and particle size as CQA was described in the design space using design of experiments - one-factor response surface method. Obtained results from statistically designed experiments enabled establishment of mathematical models and equations that were used for detailed characterization of influence of identified CPP upon MDDC particle size and particle size distribution and their subsequent optimization. Copyright © 2015 Elsevier B.V. All rights reserved.

  1. Environmental restoration and statistics: Issues and needs

    International Nuclear Information System (INIS)

    Gilbert, R.O.

    1991-10-01

    Statisticians have a vital role to play in environmental restoration (ER) activities. One facet of that role is to point out where additional work is needed to develop statistical sampling plans and data analyses that meet the needs of ER. This paper is an attempt to show where statistics fits into the ER process. The statistician, as member of the ER planning team, works collaboratively with the team to develop the site characterization sampling design, so that data of the quality and quantity required by the specified data quality objectives (DQOs) are obtained. At the same time, the statistician works with the rest of the planning team to design and implement, when appropriate, the observational approach to streamline the ER process and reduce costs. The statistician will also provide the expertise needed to select or develop appropriate tools for statistical analysis that are suited for problems that are common to waste-site data. These data problems include highly heterogeneous waste forms, large variability in concentrations over space, correlated data, data that do not have a normal (Gaussian) distribution, and measurements below detection limits. Other problems include environmental transport and risk models that yield highly uncertain predictions, and the need to effectively communicate to the public highly technical information, such as sampling plans, site characterization data, statistical analysis results, and risk estimates. Even though some statistical analysis methods are available ''off the shelf'' for use in ER, these problems require the development of additional statistical tools, as discussed in this paper. 29 refs

  2. Statistical learning and prejudice.

    Science.gov (United States)

    Madison, Guy; Ullén, Fredrik

    2012-12-01

    Human behavior is guided by evolutionarily shaped brain mechanisms that make statistical predictions based on limited information. Such mechanisms are important for facilitating interpersonal relationships, avoiding dangers, and seizing opportunities in social interaction. We thus suggest that it is essential for analyses of prejudice and prejudice reduction to take the predictive accuracy and adaptivity of the studied prejudices into account.

  3. Statistical mechanics

    CERN Document Server

    Schwabl, Franz

    2006-01-01

    The completely revised new edition of the classical book on Statistical Mechanics covers the basic concepts of equilibrium and non-equilibrium statistical physics. In addition to a deductive approach to equilibrium statistics and thermodynamics based on a single hypothesis - the form of the microcanonical density matrix - this book treats the most important elements of non-equilibrium phenomena. Intermediate calculations are presented in complete detail. Problems at the end of each chapter help students to consolidate their understanding of the material. Beyond the fundamentals, this text demonstrates the breadth of the field and its great variety of applications. Modern areas such as renormalization group theory, percolation, stochastic equations of motion and their applications to critical dynamics, kinetic theories, as well as fundamental considerations of irreversibility, are discussed. The text will be useful for advanced students of physics and other natural sciences; a basic knowledge of quantum mechan...

  4. Statistical mechanics

    CERN Document Server

    Jana, Madhusudan

    2015-01-01

    Statistical mechanics is self sufficient, written in a lucid manner, keeping in mind the exam system of the universities. Need of study this subject and its relation to Thermodynamics is discussed in detail. Starting from Liouville theorem gradually, the Statistical Mechanics is developed thoroughly. All three types of Statistical distribution functions are derived separately with their periphery of applications and limitations. Non-interacting ideal Bose gas and Fermi gas are discussed thoroughly. Properties of Liquid He-II and the corresponding models have been depicted. White dwarfs and condensed matter physics, transport phenomenon - thermal and electrical conductivity, Hall effect, Magneto resistance, viscosity, diffusion, etc. are discussed. Basic understanding of Ising model is given to explain the phase transition. The book ends with a detailed coverage to the method of ensembles (namely Microcanonical, canonical and grand canonical) and their applications. Various numerical and conceptual problems ar...

  5. Statistical physics

    CERN Document Server

    Guénault, Tony

    2007-01-01

    In this revised and enlarged second edition of an established text Tony Guénault provides a clear and refreshingly readable introduction to statistical physics, an essential component of any first degree in physics. The treatment itself is self-contained and concentrates on an understanding of the physical ideas, without requiring a high level of mathematical sophistication. A straightforward quantum approach to statistical averaging is adopted from the outset (easier, the author believes, than the classical approach). The initial part of the book is geared towards explaining the equilibrium properties of a simple isolated assembly of particles. Thus, several important topics, for example an ideal spin-½ solid, can be discussed at an early stage. The treatment of gases gives full coverage to Maxwell-Boltzmann, Fermi-Dirac and Bose-Einstein statistics. Towards the end of the book the student is introduced to a wider viewpoint and new chapters are included on chemical thermodynamics, interactions in, for exam...

  6. Statistical Physics

    CERN Document Server

    Mandl, Franz

    1988-01-01

    The Manchester Physics Series General Editors: D. J. Sandiford; F. Mandl; A. C. Phillips Department of Physics and Astronomy, University of Manchester Properties of Matter B. H. Flowers and E. Mendoza Optics Second Edition F. G. Smith and J. H. Thomson Statistical Physics Second Edition E. Mandl Electromagnetism Second Edition I. S. Grant and W. R. Phillips Statistics R. J. Barlow Solid State Physics Second Edition J. R. Hook and H. E. Hall Quantum Mechanics F. Mandl Particle Physics Second Edition B. R. Martin and G. Shaw The Physics of Stars Second Edition A. C. Phillips Computing for Scient

  7. AP statistics

    CERN Document Server

    Levine-Wissing, Robin

    2012-01-01

    All Access for the AP® Statistics Exam Book + Web + Mobile Everything you need to prepare for the Advanced Placement® exam, in a study system built around you! There are many different ways to prepare for an Advanced Placement® exam. What's best for you depends on how much time you have to study and how comfortable you are with the subject matter. To score your highest, you need a system that can be customized to fit you: your schedule, your learning style, and your current level of knowledge. This book, and the online tools that come with it, will help you personalize your AP® Statistics prep

  8. Statistical mechanics

    CERN Document Server

    Davidson, Norman

    2003-01-01

    Clear and readable, this fine text assists students in achieving a grasp of the techniques and limitations of statistical mechanics. The treatment follows a logical progression from elementary to advanced theories, with careful attention to detail and mathematical development, and is sufficiently rigorous for introductory or intermediate graduate courses.Beginning with a study of the statistical mechanics of ideal gases and other systems of non-interacting particles, the text develops the theory in detail and applies it to the study of chemical equilibrium and the calculation of the thermody

  9. The statistical process control methods - SPC

    Directory of Open Access Journals (Sweden)

    Floreková Ľubica

    1998-03-01

    Full Text Available Methods of statistical evaluation of quality – SPC (item 20 of the documentation system of quality control of ISO norm, series 900 of various processes, products and services belong amongst basic qualitative methods that enable us to analyse and compare data pertaining to various quantitative parameters. Also they enable, based on the latter, to propose suitable interventions with the aim of improving these processes, products and services. Theoretical basis and applicatibily of the principles of the: - diagnostics of a cause and effects, - Paret analysis and Lorentz curve, - number distribution and frequency curves of random variable distribution, - Shewhart regulation charts, are presented in the contribution.

  10. Applications of MIDAS regression in analysing trends in water quality

    Science.gov (United States)

    Penev, Spiridon; Leonte, Daniela; Lazarov, Zdravetz; Mann, Rob A.

    2014-04-01

    We discuss novel statistical methods in analysing trends in water quality. Such analysis uses complex data sets of different classes of variables, including water quality, hydrological and meteorological. We analyse the effect of rainfall and flow on trends in water quality utilising a flexible model called Mixed Data Sampling (MIDAS). This model arises because of the mixed frequency in the data collection. Typically, water quality variables are sampled fortnightly, whereas the rain data is sampled daily. The advantage of using MIDAS regression is in the flexible and parsimonious modelling of the influence of the rain and flow on trends in water quality variables. We discuss the model and its implementation on a data set from the Shoalhaven Supply System and Catchments in the state of New South Wales, Australia. Information criteria indicate that MIDAS modelling improves upon simplistic approaches that do not utilise the mixed data sampling nature of the data.

  11. Statistical Computing

    Indian Academy of Sciences (India)

    inference and finite population sampling. Sudhakar Kunte. Elements of statistical computing are discussed in this series. ... which captain gets an option to decide whether to field first or bat first ... may of course not be fair, in the sense that the team which wins ... describe two methods of drawing a random number between 0.

  12. Statistical thermodynamics

    CERN Document Server

    Schrödinger, Erwin

    1952-01-01

    Nobel Laureate's brilliant attempt to develop a simple, unified standard method of dealing with all cases of statistical thermodynamics - classical, quantum, Bose-Einstein, Fermi-Dirac, and more.The work also includes discussions of Nernst theorem, Planck's oscillator, fluctuations, the n-particle problem, problem of radiation, much more.

  13. The variability problem of normal human walking

    DEFF Research Database (Denmark)

    Simonsen, Erik B; Alkjær, Tine

    2012-01-01

    Previous investigations have suggested considerable inter-individual variability in the time course pattern of net joint moments during normal human walking, although the limited sample sizes precluded statistical analyses. The purpose of the present study was to obtain joint moment patterns from...... a group of normal subjects and to test whether or not the expected differences would prove to be statistically significant. Fifteen healthy male subjects were recorded on video while they walked across two force platforms. Ten kinematic and kinetic parameters were selected and input to a statistical...... cluster analysis to determine whether or not the 15 subjects could be divided into different 'families' (clusters) of walking strategy. The net joint moments showed a variability corroborating earlier reports. The cluster analysis showed that the 15 subjects could be grouped into two clusters of 5 and 10...

  14. ESEARCH OF THE LAW OF DISTRIBUTION OF THE RANDOM VARIABLE OF THE COMPRESSION

    Directory of Open Access Journals (Sweden)

    I. Sarayeva

    2011-01-01

    Full Text Available At research of diagnosing the process of modern automobile engines by means of methods of mathematical statistics the experimental data of the random variable of compression are analysed and it is proved that the random variable of compression has the form of the normal law of distribution.

  15. Wind Patterns of Coastal Tanzania: Their Variability and Trends

    African Journals Online (AJOL)

    Abstract—Patterns in Tanzanian coastal winds were investigated in terms of their variability at the weather stations of Tanga, Zanzibar, Dar es Salaam and Mtwara. Three-hourly data collected over a 30-year period (1977-2006) were used for the study. Statistical analyses included regressions, correlations, spectral analysis,.

  16. Statistics II essentials

    CERN Document Server

    Milewski, Emil G

    2012-01-01

    REA's Essentials provide quick and easy access to critical information in a variety of different fields, ranging from the most basic to the most advanced. As its name implies, these concise, comprehensive study guides summarize the essentials of the field covered. Essentials are helpful when preparing for exams, doing homework and will remain a lasting reference source for students, teachers, and professionals. Statistics II discusses sampling theory, statistical inference, independent and dependent variables, correlation theory, experimental design, count data, chi-square test, and time se

  17. Energy Statistics

    International Nuclear Information System (INIS)

    Anon.

    1994-01-01

    For the years 1992 and 1993, part of the figures shown in the tables of the Energy Review are preliminary or estimated. The annual statistics of the Energy Review appear in more detail from the publication Energiatilastot - Energy Statistics issued annually, which also includes historical time series over a longer period. The tables and figures shown in this publication are: Changes in the volume of GNP and energy consumption; Coal consumption; Natural gas consumption; Peat consumption; Domestic oil deliveries; Import prices of oil; Price development of principal oil products; Fuel prices for power production; Total energy consumption by source; Electricity supply; Energy imports by country of origin in 1993; Energy exports by recipient country in 1993; Consumer prices of liquid fuels; Consumer prices of hard coal and natural gas, prices of indigenous fuels; Average electricity price by type of consumer; Price of district heating by type of consumer and Excise taxes and turnover taxes included in consumer prices of some energy sources

  18. Statistical Optics

    Science.gov (United States)

    Goodman, Joseph W.

    2000-07-01

    The Wiley Classics Library consists of selected books that have become recognized classics in their respective fields. With these new unabridged and inexpensive editions, Wiley hopes to extend the life of these important works by making them available to future generations of mathematicians and scientists. Currently available in the Series: T. W. Anderson The Statistical Analysis of Time Series T. S. Arthanari & Yadolah Dodge Mathematical Programming in Statistics Emil Artin Geometric Algebra Norman T. J. Bailey The Elements of Stochastic Processes with Applications to the Natural Sciences Robert G. Bartle The Elements of Integration and Lebesgue Measure George E. P. Box & Norman R. Draper Evolutionary Operation: A Statistical Method for Process Improvement George E. P. Box & George C. Tiao Bayesian Inference in Statistical Analysis R. W. Carter Finite Groups of Lie Type: Conjugacy Classes and Complex Characters R. W. Carter Simple Groups of Lie Type William G. Cochran & Gertrude M. Cox Experimental Designs, Second Edition Richard Courant Differential and Integral Calculus, Volume I RIchard Courant Differential and Integral Calculus, Volume II Richard Courant & D. Hilbert Methods of Mathematical Physics, Volume I Richard Courant & D. Hilbert Methods of Mathematical Physics, Volume II D. R. Cox Planning of Experiments Harold S. M. Coxeter Introduction to Geometry, Second Edition Charles W. Curtis & Irving Reiner Representation Theory of Finite Groups and Associative Algebras Charles W. Curtis & Irving Reiner Methods of Representation Theory with Applications to Finite Groups and Orders, Volume I Charles W. Curtis & Irving Reiner Methods of Representation Theory with Applications to Finite Groups and Orders, Volume II Cuthbert Daniel Fitting Equations to Data: Computer Analysis of Multifactor Data, Second Edition Bruno de Finetti Theory of Probability, Volume I Bruno de Finetti Theory of Probability, Volume 2 W. Edwards Deming Sample Design in Business Research

  19. Statistical utilitarianism

    OpenAIRE

    Pivato, Marcus

    2013-01-01

    We show that, in a sufficiently large population satisfying certain statistical regularities, it is often possible to accurately estimate the utilitarian social welfare function, even if we only have very noisy data about individual utility functions and interpersonal utility comparisons. In particular, we show that it is often possible to identify an optimal or close-to-optimal utilitarian social choice using voting rules such as the Borda rule, approval voting, relative utilitarianism, or a...

  20. Experimental statistics

    CERN Document Server

    Natrella, Mary Gibbons

    1963-01-01

    Formulated to assist scientists and engineers engaged in army ordnance research and development programs, this well-known and highly regarded handbook is a ready reference for advanced undergraduate and graduate students as well as for professionals seeking engineering information and quantitative data for designing, developing, constructing, and testing equipment. Topics include characterizing and comparing the measured performance of a material, product, or process; general considerations in planning experiments; statistical techniques for analyzing extreme-value data; use of transformations

  1. Elementary Statistics Tables

    CERN Document Server

    Neave, Henry R

    2012-01-01

    This book, designed for students taking a basic introductory course in statistical analysis, is far more than just a book of tables. Each table is accompanied by a careful but concise explanation and useful worked examples. Requiring little mathematical background, Elementary Statistics Tables is thus not just a reference book but a positive and user-friendly teaching and learning aid. The new edition contains a new and comprehensive "teach-yourself" section on a simple but powerful approach, now well-known in parts of industry but less so in academia, to analysing and interpreting process dat

  2. Search Databases and Statistics

    DEFF Research Database (Denmark)

    Refsgaard, Jan C; Munk, Stephanie; Jensen, Lars J

    2016-01-01

    having strengths and weaknesses that must be considered for the individual needs. These are reviewed in this chapter. Equally critical for generating highly confident output datasets is the application of sound statistical criteria to limit the inclusion of incorrect peptide identifications from database...... searches. Additionally, careful filtering and use of appropriate statistical tests on the output datasets affects the quality of all downstream analyses and interpretation of the data. Our considerations and general practices on these aspects of phosphoproteomics data processing are presented here....

  3. MEVSİMSEL DÜZELTMEDE KULLANILAN İSTATİSTİKİ YÖNTEMLER ÜZERİNE BİR İNCELEME-AN ANALYSE ON STATISTICAL METHODS WHICH ARE USED FOR SEASONAL ADJUSTMENT

    Directory of Open Access Journals (Sweden)

    Handan YOLSAL

    2012-06-01

    Full Text Available Bu makalenin amacı zaman serileri için resmi istatistik ajansları tarafından geliştirilen ve çok yaygın olarak uygulanan mevsim düzeltme programlarını tanıtmaktır. Bu programlar iki ana grupta sınıflanmaktadır. Bunlardan biri, ilk defa olarak NBER tarafından geliştirilen ve hareketli ortalamalar filtreleri kullanan CENSUS II X-11 ailesidir. Bu aile X-11 ARIMA ve X-12 ARIMA tekniklerini içerir. Diğeri ise İspanya Merkez Bankası tarafından geliştirilen ve model bazlı bir yaklaşım olan TRAMO/SEATS programıdır. Bu makalede sözü edilen tekniklerin mevsimsel ayrıştırma süreçleri, bu tekniklerin içerdiği ticari gün, takvim etkisi gibi bazı özel etkiler, avantaj ve dezavantajları ve ayrıca öngörü performansları tartışılacaktır.-This paper’s aim is to introduce most commonly applied seasonal adjustment programs improved by official statistical agencies for the time series. These programs are classified in two main groups. One of them is the family of  CENSUS II X-11 which was using moving average filters and was first developed by NBER. This family involves X-11 ARIMA and X-12 ARIMA techniques. The other one is TRAMO/SEATS program which was a model based approach and has been developed by Spain Central Bank. The seasonal decomposition procedures of these techniques which are mentioned before and consisting of some special effects such as trading day, calendar effects and their advantages-disadvantages and also forecasting performances of them will be discussed in this paper.

  4. Energy statistics

    International Nuclear Information System (INIS)

    Anon.

    1989-01-01

    World data from the United Nation's latest Energy Statistics Yearbook, first published in our last issue, are completed here. The 1984-86 data were revised and 1987 data added for world commercial energy production and consumption, world natural gas plant liquids production, world LP-gas production, imports, exports, and consumption, world residual fuel oil production, imports, exports, and consumption, world lignite production, imports, exports, and consumption, world peat production and consumption, world electricity production, imports, exports, and consumption (Table 80), and world nuclear electric power production

  5. Statistics I essentials

    CERN Document Server

    Milewski, Emil G

    2012-01-01

    REA's Essentials provide quick and easy access to critical information in a variety of different fields, ranging from the most basic to the most advanced. As its name implies, these concise, comprehensive study guides summarize the essentials of the field covered. Essentials are helpful when preparing for exams, doing homework and will remain a lasting reference source for students, teachers, and professionals. Statistics I covers include frequency distributions, numerical methods of describing data, measures of variability, parameters of distributions, probability theory, and distributions.

  6. Microvariability in AGNs: study of different statistical methods - I. Observational analysis

    Science.gov (United States)

    Zibecchi, L.; Andruchow, I.; Cellone, S. A.; Carpintero, D. D.; Romero, G. E.; Combi, J. A.

    2017-05-01

    We present the results of a study of different statistical methods currently used in the literature to analyse the (micro)variability of active galactic nuclei (AGNs) from ground-based optical observations. In particular, we focus on the comparison between the results obtained by applying the so-called C and F statistics, which are based on the ratio of standard deviations and variances, respectively. The motivation for this is that the implementation of these methods leads to different and contradictory results, making the variability classification of the light curves of a certain source dependent on the statistics implemented. For this purpose, we re-analyse the results on an AGN sample observed along several sessions with the 2.15 m 'Jorge Sahade' telescope (CASLEO), San Juan, Argentina. For each AGN, we constructed the nightly differential light curves. We thus obtained a total of 78 light curves for 39 AGNs, and we then applied the statistical tests mentioned above, in order to re-classify the variability state of these light curves and in an attempt to find the suitable statistical methodology to study photometric (micro)variations. We conclude that, although the C criterion is not proper a statistical test, it could still be a suitable parameter to detect variability and that its application allows us to get more reliable variability results, in contrast with the F test.

  7. The analysis of morphometric data on rocky mountain wolves and artic wolves using statistical method

    Science.gov (United States)

    Ammar Shafi, Muhammad; Saifullah Rusiman, Mohd; Hamzah, Nor Shamsidah Amir; Nor, Maria Elena; Ahmad, Noor’ani; Azia Hazida Mohamad Azmi, Nur; Latip, Muhammad Faez Ab; Hilmi Azman, Ahmad

    2018-04-01

    Morphometrics is a quantitative analysis depending on the shape and size of several specimens. Morphometric quantitative analyses are commonly used to analyse fossil record, shape and size of specimens and others. The aim of the study is to find the differences between rocky mountain wolves and arctic wolves based on gender. The sample utilised secondary data which included seven variables as independent variables and two dependent variables. Statistical modelling was used in the analysis such was the analysis of variance (ANOVA) and multivariate analysis of variance (MANOVA). The results showed there exist differentiating results between arctic wolves and rocky mountain wolves based on independent factors and gender.

  8. Statistical analysis of management data

    CERN Document Server

    Gatignon, Hubert

    2013-01-01

    This book offers a comprehensive approach to multivariate statistical analyses. It provides theoretical knowledge of the concepts underlying the most important multivariate techniques and an overview of actual applications.

  9. Multivariate Statistical Process Control

    DEFF Research Database (Denmark)

    Kulahci, Murat

    2013-01-01

    As sensor and computer technology continues to improve, it becomes a normal occurrence that we confront with high dimensional data sets. As in many areas of industrial statistics, this brings forth various challenges in statistical process control (SPC) and monitoring for which the aim...... is to identify “out-of-control” state of a process using control charts in order to reduce the excessive variation caused by so-called assignable causes. In practice, the most common method of monitoring multivariate data is through a statistic akin to the Hotelling’s T2. For high dimensional data with excessive...... amount of cross correlation, practitioners are often recommended to use latent structures methods such as Principal Component Analysis to summarize the data in only a few linear combinations of the original variables that capture most of the variation in the data. Applications of these control charts...

  10. Order, disorder and generalized statistics

    International Nuclear Information System (INIS)

    Marino, E.C.; Swieca, J.A.

    1980-06-01

    We generalize the prescription of Kadanoff and Ceva for the computation of disorder variables correlation functions in the Ising model for continuous field theories with U(1) symmetry. By considering the product of order and disorder variables, we obtain a path integral representation for fields with generalized statistics. We discuss in detail the cases of massless Thirring and Schwinger models. (Author) [pt

  11. Statistical Models for Social Networks

    NARCIS (Netherlands)

    Snijders, Tom A. B.; Cook, KS; Massey, DS

    2011-01-01

    Statistical models for social networks as dependent variables must represent the typical network dependencies between tie variables such as reciprocity, homophily, transitivity, etc. This review first treats models for single (cross-sectionally observed) networks and then for network dynamics. For

  12. Order, disorder and generalized statistics

    International Nuclear Information System (INIS)

    Marino, E.C.; Swieca, J.A.; Pontificia Universidade Catolica do Rio de Janeiro

    1980-01-01

    We generalize the prescription of Kadanoff and Ceva for the computation of disorder variable correlation functions in the Ising model for continuous field theories with U(1) symmetry. By considering the product of order and disorder variables, we obtain a path integral representation for fields with generalized statistics. We discuss in detail the cases of massless Thirring and Schwinger models. (orig.)

  13. Synoptic climatological analyses on the seasonal transition from winter to spring in Europe also with attention to the day-to-day variability (Comparing with that in East Asia)

    Science.gov (United States)

    Kato, Kuranoshin; Hamaki, Tatsuya; Haga, Yuichi; Otani, Kazuo; Kato, Haruko

    2016-04-01

    There are many stages with rapid seasonal transitions in East Asia, greatly influenced by the considerable phase differences of seasonal cycle among the Asian monsoon subsystems, resulting in the variety of "seasonal feeling". The seasonal cycle has been an important background for generation of the many kinds of arts also in Europe around the western edge of the Eurasian Continent. Especially around Germany, there are so many music or literature works in which the "May" is treated as the special season. However, more detailed examination and its comparison with that in East Asia about the seasonal evolution from winter to spring including before May would be interesting. Deeper knowledge on the seasonal cycle would contribute greatly to the cultural understanding as mentioned above, as well as for considering the detailed response of the regional climate to the global-scale impacts such as the global warming. As such, the present study examined, based mainly on the NCEP/NCAR reanalysis data during 1971-2010, the synoptic climatological features on the seasonal transition from winter to spring in Europe also with attention to the day-to-day variability, by comparing with those in East Asia (detailed analyses were made mainly for 2000/01 - 2010/11 winters). Around the region from Germany to Turkey, the surface air temperature (TS) showed rather larger day-to-day variation (including the interannual or intraseasonal variation) throughout a year than in the Japan Islands area in East Asia. Especially from December to March (the minimum period of the climatological TS in the European side), the day-to-day variation was extremely great around Germany and its northern region (to the north of around 45N/10E). Thus, the extremely low temperature events sometimes appeared around Germany till the end of March, although the seasonal mean TS was not so considerably low. The day-to-day variation of sea level pressure (SLP) was also very large where such large amplitude of TS

  14. Statistical inference for the lifetime performance index based on generalised order statistics from exponential distribution

    Science.gov (United States)

    Vali Ahmadi, Mohammad; Doostparast, Mahdi; Ahmadi, Jafar

    2015-04-01

    In manufacturing industries, the lifetime of an item is usually characterised by a random variable X and considered to be satisfactory if X exceeds a given lower lifetime limit L. The probability of a satisfactory item is then ηL := P(X ≥ L), called conforming rate. In industrial companies, however, the lifetime performance index, proposed by Montgomery and denoted by CL, is widely used as a process capability index instead of the conforming rate. Assuming a parametric model for the random variable X, we show that there is a connection between the conforming rate and the lifetime performance index. Consequently, the statistical inferences about ηL and CL are equivalent. Hence, we restrict ourselves to statistical inference for CL based on generalised order statistics, which contains several ordered data models such as usual order statistics, progressively Type-II censored data and records. Various point and interval estimators for the parameter CL are obtained and optimal critical regions for the hypothesis testing problems concerning CL are proposed. Finally, two real data-sets on the lifetimes of insulating fluid and ball bearings, due to Nelson (1982) and Caroni (2002), respectively, and a simulated sample are analysed.

  15. Analysis of the relationship between relative abundance of mature, impregnated females of Pleoticus muelleri (Bate, 1888 (Crustacea, Decapoda and environmental variables through statistical models Análisis de la relación entre la abundancia relativa de las hembras maduras e impregnadas de Pleoticus muelleri (Bate, 1888 (Crustácea, Decapoda y las variables ambientales aplicando modelos estadísticos

    Directory of Open Access Journals (Sweden)

    Mónica Fernández

    2011-01-01

    Full Text Available The relationship between the relative abundance of mature and impregnated females of the Argentine red shrimp Pleoticus muelleri (Bate 1888 and environmental variables was analyzed using statistical methods. Analyzed data carne from the research cruises of the Instituto Nacional de Investigación y Desarrollo Pesquero (INIDEP carned out durmg January 2000, 2001, 2005, and 2007; March 2006; and November 2004, 2005, and 2006 in San Jorge Gulf (Argentina. The biological variables considered were the relative abundances of mature and impregnated female shrimp, whereas the environmental variables corresponded to depth, bottom water temperature and salinity, and the difference between surface and bottom water temperature and salinity. Generalized additive models were used as an exploratory tool for the numerical data and the general linear models as a confirmatory tool. The results showed that the distributions and abundances of mature and impregnated females were related to the bottom water temperature and salinity and to depth. The relationship increased along with temperature; with salinity, however, it decreased for mature females and increased for impregnated females. An optimal depth range was evidenced, where the largest concentrations of these individuáis were located.Se presenta el análisis de la relación entre la abundancia relativa de las hembras maduras e impregnadas del langostino Pleoticus muelleri (Bate, 1888 y las variables ambientales, mediante la aplicación de modelos estadísticos. Los datos analizados provienen de las campañas de investigación del Instituto Nacional de Investigación y Desarrollo Pesquero (INIDEP realizadas en enero de 2000, 2001, 2005 y 2007, marzo de 2006 y noviembre de 2004, 2005 y 2006 en el Golfo San Jorge (Argentina. Se consideraron las variables biológicas: abundancia relativa de hembras maduras y de hembras impregnadas de langostino y las variables ambientales: profundidad, temperatura y salinidad

  16. An analysis of distribution transformer failure using the statistical package for the social sciences (SPSS software

    Directory of Open Access Journals (Sweden)

    María Gabriela Mago Ramos

    2012-05-01

    Full Text Available A methodology was developed for analysing faults in distribution transformers using the statistical package for social sciences (SPSS; it consisted of organising and creating of database regarding failed equipment, incorporating such data into the processing programme and converting all the information into numerical variables to be processed, thereby obtaining descriptive statistics and enabling factor and discriminant analysis. The research was based on information provided by companies in areas served by Corpoelec (Valencia, Venezuela and Codensa (Bogotá, Colombia.

  17. Collective variables and dissipation

    International Nuclear Information System (INIS)

    Balian, R.

    1984-09-01

    This is an introduction to some basic concepts of non-equilibrium statistical mechanics. We emphasize in particular the relevant entropy relative to a given set of collective variables, the meaning of the projection method in the Liouville space, its use to establish the generalized transport equations for these variables, and the interpretation of dissipation in the framework of information theory

  18. National Statistical Commission and Indian Official Statistics*

    Indian Academy of Sciences (India)

    IAS Admin

    a good collection of official statistics of that time. With more .... statistical agencies and institutions to provide details of statistical activities .... ing several training programmes. .... ful completion of Indian Statistical Service examinations, the.

  19. Statistical methods for quantitative indicators of impacts, applied to transmission line projects

    International Nuclear Information System (INIS)

    Ospina Norena, Jesus Efren; Lema Tapias, Alvaro de Jesus

    2005-01-01

    Multivariate statistical analyses are proposed for encountering the relationships between variables and impacts, to obtain high explanatory power for interpretation of the causes and effects and achieve the highest certainty possible, to evaluate and classify impacts by their level of influence

  20. Intuitive introductory statistics

    CERN Document Server

    Wolfe, Douglas A

    2017-01-01

    This textbook is designed to give an engaging introduction to statistics and the art of data analysis. The unique scope includes, but also goes beyond, classical methodology associated with the normal distribution. What if the normal model is not valid for a particular data set? This cutting-edge approach provides the alternatives. It is an introduction to the world and possibilities of statistics that uses exercises, computer analyses, and simulations throughout the core lessons. These elementary statistical methods are intuitive. Counting and ranking features prominently in the text. Nonparametric methods, for instance, are often based on counts and ranks and are very easy to integrate into an introductory course. The ease of computation with advanced calculators and statistical software, both of which factor into this text, allows important techniques to be introduced earlier in the study of statistics. This book's novel scope also includes measuring symmetry with Walsh averages, finding a nonp...

  1. A statistical manual for chemists

    CERN Document Server

    Bauer, Edward

    1971-01-01

    A Statistical Manual for Chemists, Second Edition presents simple and fast statistical tools for data analysis of working chemists. This edition is organized into nine chapters and begins with an overview of the fundamental principles of the statistical techniques used in experimental data analysis. The subsequent chapters deal with the concept of statistical average, experimental design, and analysis of variance. The discussion then shifts to control charts, with particular emphasis on variable charts that are more useful to chemists and chemical engineers. A chapter focuses on the effect

  2. DESIGNING ENVIRONMENTAL MONITORING DATABASES FOR STATISTIC ASSESSMENT

    Science.gov (United States)

    Databases designed for statistical analyses have characteristics that distinguish them from databases intended for general use. EMAP uses a probabilistic sampling design to collect data to produce statistical assessments of environmental conditions. In addition to supporting the ...

  3. Stupid statistics!

    Science.gov (United States)

    Tellinghuisen, Joel

    2008-01-01

    The method of least squares is probably the most powerful data analysis tool available to scientists. Toward a fuller appreciation of that power, this work begins with an elementary review of statistics fundamentals, and then progressively increases in sophistication as the coverage is extended to the theory and practice of linear and nonlinear least squares. The results are illustrated in application to data analysis problems important in the life sciences. The review of fundamentals includes the role of sampling and its connection to probability distributions, the Central Limit Theorem, and the importance of finite variance. Linear least squares are presented using matrix notation, and the significance of the key probability distributions-Gaussian, chi-square, and t-is illustrated with Monte Carlo calculations. The meaning of correlation is discussed, including its role in the propagation of error. When the data themselves are correlated, special methods are needed for the fitting, as they are also when fitting with constraints. Nonlinear fitting gives rise to nonnormal parameter distributions, but the 10% Rule of Thumb suggests that such problems will be insignificant when the parameter is sufficiently well determined. Illustrations include calibration with linear and nonlinear response functions, the dangers inherent in fitting inverted data (e.g., Lineweaver-Burk equation), an analysis of the reliability of the van't Hoff analysis, the problem of correlated data in the Guggenheim method, and the optimization of isothermal titration calorimetry procedures using the variance-covariance matrix for experiment design. The work concludes with illustrations on assessing and presenting results.

  4. Statistical Data Editing in Scientific Articles.

    Science.gov (United States)

    Habibzadeh, Farrokh

    2017-07-01

    Scientific journals are important scholarly forums for sharing research findings. Editors have important roles in safeguarding standards of scientific publication and should be familiar with correct presentation of results, among other core competencies. Editors do not have access to the raw data and should thus rely on clues in the submitted manuscripts. To identify probable errors, they should look for inconsistencies in presented results. Common statistical problems that can be picked up by a knowledgeable manuscript editor are discussed in this article. Manuscripts should contain a detailed section on statistical analyses of the data. Numbers should be reported with appropriate precisions. Standard error of the mean (SEM) should not be reported as an index of data dispersion. Mean (standard deviation [SD]) and median (interquartile range [IQR]) should be used for description of normally and non-normally distributed data, respectively. If possible, it is better to report 95% confidence interval (CI) for statistics, at least for main outcome variables. And, P values should be presented, and interpreted with caution, if there is a hypothesis. To advance knowledge and skills of their members, associations of journal editors are better to develop training courses on basic statistics and research methodology for non-experts. This would in turn improve research reporting and safeguard the body of scientific evidence. © 2017 The Korean Academy of Medical Sciences.

  5. SWORDS: A statistical tool for analysing large DNA sequences

    Indian Academy of Sciences (India)

    Unknown

    These techniques are based on frequency distributions of DNA words in a large sequence, and have been packaged into a software called SWORDS. Using sequences available in ... tions with the cellular processes like recombination, replication .... in DNA sequences using certain specific probability laws. (Pevzner et al ...

  6. Statistical methods for analysing responses of wildlife to human disturbance.

    Science.gov (United States)

    Haiganoush K. Preisler; Alan A. Ager; Michael J. Wisdom

    2006-01-01

    1. Off-road recreation is increasing rapidly in many areas of the world, and effects on wildlife can be highly detrimental. Consequently, we have developed methods for studying wildlife responses to off-road recreation with the use of new technologies that allow frequent and accurate monitoring of human-wildlife interactions. To illustrate these methods, we studied the...

  7. Statistical analyses of local transport coefficients in Ohmic ASDEX discharges

    International Nuclear Information System (INIS)

    Simmet, E.; Stroth, U.; Wagner, F.; Fahrbach, H.U.; Herrmann, W.; Kardaun, O.J.W.F.; Mayer, H.M.

    1991-01-01

    Tokamak energy transport is still an unsolved problem. Many theoretical models have been developed, which try to explain the anomalous high energy-transport coefficients. Up to now these models have been applied to global plasma parameters. A comparison of transport coefficients with global confinement time is only conclusive if the transport is dominated by one process across the plasma diameter. This, however, is not the case in most Ohmic confinement regimes, where at least three different transport mechanisms play an important role. Sawtooth activity leads to an increase in energy transport in the plasma centre. In the intermediate region turbulent transport is expected. Candidates here are drift waves and resistive fluid turbulences. At the edge, ballooning modes or rippling modes could dominate the transport. For the intermediate region, one can deduce theoretical scaling laws for τ E from turbulent theories. Predicted scalings reproduce the experimentally found density dependence of τ E in the linear Ohmic confinement regime (LOC) and the saturated regime (SOC), but they do not show the correct dependence on the isotope mass. The relevance of these transport theories can only be tested in comparing them to experimental local transport coefficients. To this purpose we have performed transport calculations on more than a hundred Ohmic ASDEX discharges. By Principal Component Analysis we determine the dimensionless components which dominate the transport coefficients and we compare the results to the predictions of various theories. (author) 6 refs., 2 figs., 1 tab

  8. Statistical considerations for grain-size analyses of tills

    Science.gov (United States)

    Jacobs, A.M.

    1971-01-01

    Relative percentages of sand, silt, and clay from samples of the same till unit are not identical because of different lithologies in the source areas, sorting in transport, random variation, and experimental error. Random variation and experimental error can be isolated from the other two as follows. For each particle-size class of each till unit, a standard population is determined by using a normally distributed, representative group of data. New measurements are compared with the standard population and, if they compare satisfactorily, the experimental error is not significant and random variation is within the expected range for the population. The outcome of the comparison depends on numerical criteria derived from a graphical method rather than on a more commonly used one-way analysis of variance with two treatments. If the number of samples and the standard deviation of the standard population are substituted in a t-test equation, a family of hyperbolas is generated, each of which corresponds to a specific number of subsamples taken from each new sample. The axes of the graphs of the hyperbolas are the standard deviation of new measurements (horizontal axis) and the difference between the means of the new measurements and the standard population (vertical axis). The area between the two branches of each hyperbola corresponds to a satisfactory comparison between the new measurements and the standard population. Measurements from a new sample can be tested by plotting their standard deviation vs. difference in means on axes containing a hyperbola corresponding to the specific number of subsamples used. If the point lies between the branches of the hyperbola, the measurements are considered reliable. But if the point lies outside this region, the measurements are repeated. Because the critical segment of the hyperbola is approximately a straight line parallel to the horizontal axis, the test is simplified to a comparison between the means of the standard population and the means of the subsample. The minimum number of subsamples required to prove significant variation between samples caused by different lithologies in the source areas and sorting in transport can be determined directly from the graphical method. The minimum number of subsamples required is the maximum number to be run for economy of effort. ?? 1971 Plenum Publishing Corporation.

  9. Practical Statistics for Particle Physics Analyses: Likelihoods (1/4)

    CERN Multimedia

    CERN. Geneva; Lyons, Louis

    2016-01-01

    This will be a 4-day series of 2-hour sessions as part of CERN's Academic Training Course. Each session will consist of a 1-hour lecture followed by one hour of practical computing, which will have exercises based on that day's lecture. While it is possible to follow just the lectures or just the computing exercises, we highly recommend that, because of the way this course is designed, participants come to both parts. In order to follow the hands-on exercises sessions, students need to bring their own laptops. The exercises will be run on a dedicated CERN Web notebook service, SWAN (swan.cern.ch), which is open to everybody holding a CERN computing account. The requirement to use the SWAN service is to have a CERN account and to have also access to Cernbox, the shared storage service at CERN. New users of cernbox are invited to activate beforehand cernbox by simply connecting to https://cernbox.cern.ch. A basic prior knowledge of ROOT and C++ is also recommended for participation in the practical session....

  10. Late neolithic pottery standardization: Application of statistical analyses

    Directory of Open Access Journals (Sweden)

    Vuković Jasna

    2011-01-01

    Full Text Available This paper defines the notion of standardization, presents the methodological approach to analysis, points to the problems and limitation arising in examination of materials from archaeological excavations, and presents the results of the analysis of coefficients of variation of metric parameters of the Late Neolithic vessels recovered at the sites of Vinča and Motel Slatina. [Projekat Ministarstva nauke Republike Srbije, br. 177012: Society, the spiritual and material culture and communications in prehistory and early history of the Balkans

  11. Statistical and regression analyses of detected extrasolar systems

    Czech Academy of Sciences Publication Activity Database

    Pintr, Pavel; Peřinová, V.; Lukš, A.; Pathak, A.

    2013-01-01

    Roč. 75, č. 1 (2013), s. 37-45 ISSN 0032-0633 Institutional support: RVO:61389021 Keywords : Exoplanets * Kepler candidates * Regression analysis Subject RIV: BN - Astronomy, Celestial Mechanics, Astrophysics Impact factor: 1.630, year: 2013 http://www.sciencedirect.com/science/article/pii/S0032063312003066

  12. [Clinical research XXIII. From clinical judgment to meta-analyses].

    Science.gov (United States)

    Rivas-Ruiz, Rodolfo; Castelán-Martínez, Osvaldo D; Pérez-Rodríguez, Marcela; Palacios-Cruz, Lino; Noyola-Castillo, Maura E; Talavera, Juan O

    2014-01-01

    Systematic reviews (SR) are studies made in order to ask clinical questions based on original articles. Meta-analysis (MTA) is the mathematical analysis of SR. These analyses are divided in two groups, those which evaluate the measured results of quantitative variables (for example, the body mass index -BMI-) and those which evaluate qualitative variables (for example, if a patient is alive or dead, or if he is healing or not). Quantitative variables generally use the mean difference analysis and qualitative variables can be performed using several calculations: odds ratio (OR), relative risk (RR), absolute risk reduction (ARR) and hazard ratio (HR). These analyses are represented through forest plots which allow the evaluation of each individual study, as well as the heterogeneity between studies and the overall effect of the intervention. These analyses are mainly based on Student's t test and chi-squared. To take appropriate decisions based on the MTA, it is important to understand the characteristics of statistical methods in order to avoid misinterpretations.

  13. Statistical core design

    International Nuclear Information System (INIS)

    Oelkers, E.; Heller, A.S.; Farnsworth, D.A.; Kearfott, K.J.

    1978-01-01

    The report describes the statistical analysis of DNBR thermal-hydraulic margin of a 3800 MWt, 205-FA core under design overpower conditions. The analysis used LYNX-generated data at predetermined values of the input variables whose uncertainties were to be statistically combined. LYNX data were used to construct an efficient response surface model in the region of interest; the statistical analysis was accomplished through the evaluation of core reliability; utilizing propagation of the uncertainty distributions of the inputs. The response surface model was implemented in both the analytical error propagation and Monte Carlo Techniques. The basic structural units relating to the acceptance criteria are fuel pins. Therefore, the statistical population of pins with minimum DNBR values smaller than specified values is determined. The specified values are designated relative to the most probable and maximum design DNBR values on the power limiting pin used in present design analysis, so that gains over the present design criteria could be assessed for specified probabilistic acceptance criteria. The results are equivalent to gains ranging from 1.2 to 4.8 percent of rated power dependent on the acceptance criterion. The corresponding acceptance criteria range from 95 percent confidence that no pin will be in DNB to 99.9 percent of the pins, which are expected to avoid DNB

  14. Statistical data fusion for cross-tabulation

    NARCIS (Netherlands)

    Kamakura, W.A.; Wedel, M.

    The authors address the situation in which a researcher wants to cross-tabulate two sets of discrete variables collected in independent samples, but a subset of the variables is common to both samples. The authors propose a statistical data-fusion model that allows for statistical tests of

  15. Variables associated with active spondylolysis.

    Science.gov (United States)

    Gregg, Chris D; Dean, Sarah; Schneiders, Anthony G

    2009-11-01

    Retrospective non-experimental study. To investigate variables associated with active spondylolysis. A retrospective study audited clinical data over a two year period from patients with suspected spondylolysis that were referred for a SPECT bone scan. Six exploratory variables were identified and analysed using uni- and multi-variate regression from 82 patient records to determine the association between symptomatic, physical and demographic characteristics, and the presence of an active spondylolysis. Tertiary level multidisciplinary private practice sports medicine clinic. All patients with low back pain that required a SPECT bone scan to confirm suspected spondylolysis. 82 subjects were included in the final sample group. The six exploratory variables included Age, Gender, Injury duration, Injury onset, Sports participation and the result of the Single Leg Hyperextension Test. The dependent outcome variable was the result of the SPECT bone scan (scan-positive or scan-negative). Adolescent males had a higher incidence of spondylolysis detected by SPECT bone scan compared to other patients and a statistically significant association was demonstrated for both age (p=0.01) and gender (p=0.01). Subjects with an active spondylolysis were nearly five times more likely to be male and aged less than 20 years. Furthermore, the likelihood ratio indicated that adolescent males with suspected spondylolysis were three and a half times more likely to have a positive bone scan result. The Single Leg Hyperextension Test did not demonstrate a statistically significant association with spondylolysis (p=0.47). Clinicians assessing for a predisposition to the development of spondylolysis should consider the gender and age of the patient and not rely on the predictive ability of the Single Leg Hyperextension Test.

  16. Hidden Statistics of Schroedinger Equation

    Science.gov (United States)

    Zak, Michail

    2011-01-01

    Work was carried out in determination of the mathematical origin of randomness in quantum mechanics and creating a hidden statistics of Schr dinger equation; i.e., to expose the transitional stochastic process as a "bridge" to the quantum world. The governing equations of hidden statistics would preserve such properties of quantum physics as superposition, entanglement, and direct-product decomposability while allowing one to measure its state variables using classical methods.

  17. A primer of multivariate statistics

    CERN Document Server

    Harris, Richard J

    2014-01-01

    Drawing upon more than 30 years of experience in working with statistics, Dr. Richard J. Harris has updated A Primer of Multivariate Statistics to provide a model of balance between how-to and why. This classic text covers multivariate techniques with a taste of latent variable approaches. Throughout the book there is a focus on the importance of describing and testing one's interpretations of the emergent variables that are produced by multivariate analysis. This edition retains its conversational writing style while focusing on classical techniques. The book gives the reader a feel for why

  18. Two independent pivotal statistics that test location and misspecification and add-up to the Anderson-Rubin statistic

    NARCIS (Netherlands)

    Kleibergen, F.R.

    2002-01-01

    We extend the novel pivotal statistics for testing the parameters in the instrumental variables regression model. We show that these statistics result from a decomposition of the Anderson-Rubin statistic into two independent pivotal statistics. The first statistic is a score statistic that tests

  19. Lies, damn lies and statistics

    International Nuclear Information System (INIS)

    Jones, M.D.

    2001-01-01

    Statistics are widely employed within archaeological research. This is becoming increasingly so as user friendly statistical packages make increasingly sophisticated analyses available to non statisticians. However, all statistical techniques are based on underlying assumptions of which the end user may be unaware. If statistical analyses are applied in ignorance of the underlying assumptions there is the potential for highly erroneous inferences to be drawn. This does happen within archaeology and here this is illustrated with the example of 'date pooling', a technique that has been widely misused in archaeological research. This misuse may have given rise to an inevitable and predictable misinterpretation of New Zealand's archaeological record. (author). 10 refs., 6 figs., 1 tab

  20. Dynamic statistical information theory

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    In recent years we extended Shannon static statistical information theory to dynamic processes and established a Shannon dynamic statistical information theory, whose core is the evolution law of dynamic entropy and dynamic information. We also proposed a corresponding Boltzmman dynamic statistical information theory. Based on the fact that the state variable evolution equation of respective dynamic systems, i.e. Fokker-Planck equation and Liouville diffusion equation can be regarded as their information symbol evolution equation, we derived the nonlinear evolution equations of Shannon dynamic entropy density and dynamic information density and the nonlinear evolution equations of Boltzmann dynamic entropy density and dynamic information density, that describe respectively the evolution law of dynamic entropy and dynamic information. The evolution equations of these two kinds of dynamic entropies and dynamic informations show in unison that the time rate of change of dynamic entropy densities is caused by their drift, diffusion and production in state variable space inside the systems and coordinate space in the transmission processes; and that the time rate of change of dynamic information densities originates from their drift, diffusion and dissipation in state variable space inside the systems and coordinate space in the transmission processes. Entropy and information have been combined with the state and its law of motion of the systems. Furthermore we presented the formulas of two kinds of entropy production rates and information dissipation rates, the expressions of two kinds of drift information flows and diffusion information flows. We proved that two kinds of information dissipation rates (or the decrease rates of the total information) were equal to their corresponding entropy production rates (or the increase rates of the total entropy) in the same dynamic system. We obtained the formulas of two kinds of dynamic mutual informations and dynamic channel

  1. Statistical characterization report for Single-Shell Tank 241-T-104

    International Nuclear Information System (INIS)

    Cromar, R.D.; Wilmarth, S.R.; Jensen, L.

    1994-01-01

    This report contains the results of the statistical analysis of data from two core samples obtained from single-shell tank 241-T-104 (T-104). Section 2.0 contains a description of the core samples and the chemical analyses performed on the core samples. Section 3.0 contains mean concentration estimates and associated 95% confidence intervals (CIs) on the mean for each of the analytes found in the core composite samples. Section 4.0 contains estimates of the spatial variability (variability between cores) and estimates of the analytical variability from the core composite data. Two types of analytical variability were estimated from the core composite data: (1) sample composite variability (variability between composite samples within the same core) and (2) analytical measurement variability (variability between the primary and duplicate analyses within each core composite sample). Estimates of the analytical measurement variability were used as the reference value to test the significance of the spatial and sample composite variability. Spatial variability was significantly different from zero for 32 out of 80 analytes. The sample composite variance was significantly different from zero for 18 out of the 80 analytes

  2. Statistical characterization report for single-shell tank 241-T-111

    International Nuclear Information System (INIS)

    Cromar, R.D.; Wilmarth, S.R.

    1994-01-01

    This report contains the results of the statistical analysis of data from two core samples obtained from single-shell tank 241-T-111 (T-111). Section 2.0 contains a description of the core samples and the chemical analyses performed on the core samples. Section 3.0 contains mean concentration estimates and associated 95% confidence intervals (CIs) on the mean for each of the analytes found in the core samples from T-111. Section 4.0 contains estimates of the spatial variability (variability between cores) and estimates of the analytical variability from the core composite data. Two types of analytical variability were estimated from the core composite data: (1) sample composite variability (variability between composite samples within the same core) and (2) analytical measurement variability (variability between the primary and duplicate analyses within each core composite sample). Estimates of the analytical measurement variability were used as the reference value to test the significance of the spatial and sample composite variability. Spatial variability was significantly different from zero for 39 out of 85 analytes. The sample composite variance was significantly different from zero for (a different) 39 out of the 85 analytes

  3. Statistical analysis plan for the EuroHYP-1 trial

    DEFF Research Database (Denmark)

    Winkel, Per; Bath, Philip M; Gluud, Christian

    2017-01-01

    Score; (4) brain infarct size at 48 +/-24 hours; (5) EQ-5D-5 L score, and (6) WHODAS 2.0 score. Other outcomes are: the primary safety outcome serious adverse events; and the incremental cost-effectiveness, and cost utility ratios. The analysis sets include (1) the intention-to-treat population, and (2...... outcome), logistic regression (binary outcomes), general linear model (continuous outcomes), and the Poisson or negative binomial model (rate outcomes). DISCUSSION: Major adjustments compared with the original statistical analysis plan encompass: (1) adjustment of analyses by nationality; (2) power......) the per protocol population. The sample size is estimated to 800 patients (5% type 1 and 20% type 2 errors). All analyses are adjusted for the protocol-specified stratification variables (nationality of centre), and the minimisation variables. In the analysis, we use ordinal regression (the primary...

  4. Probability theory and mathematical statistics for engineers

    CERN Document Server

    Pugachev, V S

    1984-01-01

    Probability Theory and Mathematical Statistics for Engineers focuses on the concepts of probability theory and mathematical statistics for finite-dimensional random variables.The publication first underscores the probabilities of events, random variables, and numerical characteristics of random variables. Discussions focus on canonical expansions of random vectors, second-order moments of random vectors, generalization of the density concept, entropy of a distribution, direct evaluation of probabilities, and conditional probabilities. The text then examines projections of random vector

  5. R for statistics

    CERN Document Server

    Cornillon, Pierre-Andre; Husson, Francois; Jegou, Nicolas; Josse, Julie; Kloareg, Maela; Matzner-Lober, Eric; Rouviere, Laurent

    2012-01-01

    An Overview of RMain ConceptsInstalling RWork SessionHelpR ObjectsFunctionsPackagesExercisesPreparing DataReading Data from FileExporting ResultsManipulating VariablesManipulating IndividualsConcatenating Data TablesCross-TabulationExercisesR GraphicsConventional Graphical FunctionsGraphical Functions with latticeExercisesMaking Programs with RControl FlowsPredefined FunctionsCreating a FunctionExercisesStatistical MethodsIntroduction to the Statistical MethodsA Quick Start with RInstalling ROpening and Closing RThe Command PromptAttribution, Objects, and FunctionSelectionOther Rcmdr PackageImporting (or Inputting) DataGraphsStatistical AnalysisHypothesis TestConfidence Intervals for a MeanChi-Square Test of IndependenceComparison of Two MeansTesting Conformity of a ProportionComparing Several ProportionsThe Power of a TestRegressionSimple Linear RegressionMultiple Linear RegressionPartial Least Squares (PLS) RegressionAnalysis of Variance and CovarianceOne-Way Analysis of VarianceMulti-Way Analysis of Varian...

  6. [Statistics for statistics?--Thoughts about psychological tools].

    Science.gov (United States)

    Berger, Uwe; Stöbel-Richter, Yve

    2007-12-01

    Statistical methods take a prominent place among psychologists' educational programs. Being known as difficult to understand and heavy to learn, students fear of these contents. Those, who do not aspire after a research carrier at the university, will forget the drilled contents fast. Furthermore, because it does not apply for the work with patients and other target groups at a first glance, the methodological education as a whole was often questioned. For many psychological practitioners the statistical education makes only sense by enforcing respect against other professions, namely physicians. For the own business, statistics is rarely taken seriously as a professional tool. The reason seems to be clear: Statistics treats numbers, while psychotherapy treats subjects. So, does statistics ends in itself? With this article, we try to answer the question, if and how statistical methods were represented within the psychotherapeutical and psychological research. Therefore, we analyzed 46 Originals of a complete volume of the journal Psychotherapy, Psychosomatics, Psychological Medicine (PPmP). Within the volume, 28 different analyse methods were applied, from which 89 per cent were directly based upon statistics. To be able to write and critically read Originals as a backbone of research, presumes a high degree of statistical education. To ignore statistics means to ignore research and at least to reveal the own professional work to arbitrariness.

  7. Statistics for Learning Genetics

    Science.gov (United States)

    Charles, Abigail Sheena

    This study investigated the knowledge and skills that biology students may need to help them understand statistics/mathematics as it applies to genetics. The data are based on analyses of current representative genetics texts, practicing genetics professors' perspectives, and more directly, students' perceptions of, and performance in, doing statistically-based genetics problems. This issue is at the emerging edge of modern college-level genetics instruction, and this study attempts to identify key theoretical components for creating a specialized biological statistics curriculum. The goal of this curriculum will be to prepare biology students with the skills for assimilating quantitatively-based genetic processes, increasingly at the forefront of modern genetics. To fulfill this, two college level classes at two universities were surveyed. One university was located in the northeastern US and the other in the West Indies. There was a sample size of 42 students and a supplementary interview was administered to a select 9 students. Interviews were also administered to professors in the field in order to gain insight into the teaching of statistics in genetics. Key findings indicated that students had very little to no background in statistics (55%). Although students did perform well on exams with 60% of the population receiving an A or B grade, 77% of them did not offer good explanations on a probability question associated with the normal distribution provided in the survey. The scope and presentation of the applicable statistics/mathematics in some of the most used textbooks in genetics teaching, as well as genetics syllabi used by instructors do not help the issue. It was found that the text books, often times, either did not give effective explanations for students, or completely left out certain topics. The omission of certain statistical/mathematical oriented topics was seen to be also true with the genetics syllabi reviewed for this study. Nonetheless

  8. Childhood Cancer Statistics

    Science.gov (United States)

    ... Watchdog Ratings Feedback Contact Select Page Childhood Cancer Statistics Home > Cancer Resources > Childhood Cancer Statistics Childhood Cancer Statistics – Graphs and Infographics Number of Diagnoses Incidence Rates ...

  9. Statistical analysis and data management

    International Nuclear Information System (INIS)

    Anon.

    1981-01-01

    This report provides an overview of the history of the WIPP Biology Program. The recommendations of the American Institute of Biological Sciences (AIBS) for the WIPP biology program are summarized. The data sets available for statistical analyses and problems associated with these data sets are also summarized. Biological studies base maps are presented. A statistical model is presented to evaluate any correlation between climatological data and small mammal captures. No statistically significant relationship between variance in small mammal captures on Dr. Gennaro's 90m x 90m grid and precipitation records from the Duval Potash Mine were found

  10. Genetic variability and bottleneck analyses of Kanni adu goat population using microsatellite markers [Also published in The Indian Journal of Small Ruminants, 2015, 21(2): 216-22

    International Nuclear Information System (INIS)

    Jeyakumar, M.; Thiruvenkadan, R.; Saravana, R.; Periasamy, K.

    2016-01-01

    Full text: Microsatellite data on 25 loci were generated and utilized to evaluate the genetic architecture and mutation drift equilibrium of Kanni Adu goats of southern Tamil Nadu. The genetic diversity analysis of Kanni Adu goats displayed higher level of within breed variability in terms of mean number of alleles per locus (11.24±0.87) and heterozygosity values (Ho= 0.677±0.041, He=0.857±0.016). Within population inbreeding estimate (FIS=0.215±0.040) showed moderate level of inbreeding, which warrant adoption of appropriate breeding strategies under field conditions. The polymorphism information content (PIC) value ranged from 0.531 to 0.915 suggested higher polymorphism in this breed. In general, the sign, standardized differences and Wilcoxon rank tests indicated heterozygosity excess in Kanni Adu goat population in infinite alleles and two-phase model and non-significant in stepwise mutation model. Hence, the mode-shift indicator test was utilized and it indicated the absence of genetic bottleneck in the recent past in Kanni Adu goats. It suggests that any unique alleles present in this breed may not have been lost. The study indicated that Kanni adu goats exhibited substantial amount of genetic variation as reflected from the heterozygosity and number of alleles per locus. (author)

  11. Anàlisi de classificació amb variable «criteri» a SPAD

    Directory of Open Access Journals (Sweden)

    Angelina Sánchez Martí

    2018-01-01

    Full Text Available This article presents the characteristics, procedure and utility of the technique of classification analysis with criterion variable in a large set of data, using mainly categorical variables. Classification analysis forms part of the techniques commonly known as data mining that analyse relationships or associations between variables. The paper describes step by step how to apply this statistical technique with the support of SPAD software, a statistical package for multivariate analysis, and provides an example of its application. The technique is drawn from the French school of statistics. Despite being little known, it is a very useful classification analysis for working with large amounts of data, a situation that is increasingly common in educational research, and more typical of the secondary analyses that are carried out in our field.

  12. Detection and statistics of gusts

    DEFF Research Database (Denmark)

    Hannesdóttir, Ásta; Kelly, Mark C.; Mann, Jakob

    In this project, a more realistic representation of gusts, based on statistical analysis, will account for the variability observed in real-world gusts. The gust representation will focus on temporal, spatial, and velocity scales that are relevant for modern wind turbines and which possibly affect...

  13. Analysis and classification of ECG-waves and rhythms using circular statistics and vector strength

    Directory of Open Access Journals (Sweden)

    Janßen Jan-Dirk

    2017-09-01

    Full Text Available The most common way to analyse heart rhythm is to calculate the RR-interval and the heart rate variability. For further evaluation, descriptive statistics are often used. Here we introduce a new and more natural heart rhythm analysis tool that is based on circular statistics and vector strength. Vector strength is a tool to measure the periodicity or lack of periodicity of a signal. We divide the signal into non-overlapping window segments and project the detected R-waves around the unit circle using the complex exponential function and the median RR-interval. In addition, we calculate the vector strength and apply circular statistics as wells as an angular histogram on the R-wave vectors. This approach enables an intuitive visualization and analysis of rhythmicity. Our results show that ECG-waves and rhythms can be easily visualized, analysed and classified by circular statistics and vector strength.

  14. Variability Bugs:

    DEFF Research Database (Denmark)

    Melo, Jean

    . Although many researchers suggest that preprocessor-based variability amplifies maintenance problems, there is little to no hard evidence on how actually variability affects programs and programmers. Specifically, how does variability affect programmers during maintenance tasks (bug finding in particular......)? How much harder is it to debug a program as variability increases? How do developers debug programs with variability? In what ways does variability affect bugs? In this Ph.D. thesis, I set off to address such issues through different perspectives using empirical research (based on controlled...... experiments) in order to understand quantitatively and qualitatively the impact of variability on programmers at bug finding and on buggy programs. From the program (and bug) perspective, the results show that variability is ubiquitous. There appears to be no specific nature of variability bugs that could...

  15. MQSA National Statistics

    Science.gov (United States)

    ... Standards Act and Program MQSA Insights MQSA National Statistics Share Tweet Linkedin Pin it More sharing options ... but should level off with time. Archived Scorecard Statistics 2018 Scorecard Statistics 2017 Scorecard Statistics 2016 Scorecard ...

  16. State Transportation Statistics 2014

    Science.gov (United States)

    2014-12-15

    The Bureau of Transportation Statistics (BTS) presents State Transportation Statistics 2014, a statistical profile of transportation in the 50 states and the District of Columbia. This is the 12th annual edition of State Transportation Statistics, a ...

  17. Parameterization and Observability Analysis of Scalable Battery Clusters for Onboard Thermal Management Paramétrage et analyse d’observabilité de clusters de batteries de taille variable pour une gestion thermique embarquée

    Directory of Open Access Journals (Sweden)

    Lin Xinfan

    2013-03-01

    paramétrage en ligne et un observateur adaptatif sont conçus pour une batterie cylindrique. Le modèle thermique à une seule cellule est ensuite agrandi afin de créer un modèle de cluster de batteries dans le but d’étudier le schéma de température du cluster. Les interconnexions thermiques modélisées entre les cellules incluent la conduction de chaleur de cellule à cellule et la convection au flux du liquide de refroidissement environnant. Une analyse d’observabilité est effectuée sur le cluster avant la conception, pour le pack, d’un observateur en boucle fermée. Sur la base de l’analyse, les lignes directrices permettant la détermination du nombre minimal de sondes requises et leurs positionnements exacts sont déduites permettant d’assurer l’observabilité de tous les états thermiques.

  18. Predictability of the recent slowdown and subsequent recovery of large-scale surface warming using statistical methods

    Science.gov (United States)

    Mann, Michael E.; Steinman, Byron A.; Miller, Sonya K.; Frankcombe, Leela M.; England, Matthew H.; Cheung, Anson H.

    2016-04-01

    The temporary slowdown in large-scale surface warming during the early 2000s has been attributed to both external and internal sources of climate variability. Using semiempirical estimates of the internal low-frequency variability component in Northern Hemisphere, Atlantic, and Pacific surface temperatures in concert with statistical hindcast experiments, we investigate whether the slowdown and its recent recovery were predictable. We conclude that the internal variability of the North Pacific, which played a critical role in the slowdown, does not appear to have been predictable using statistical forecast methods. An additional minor contribution from the North Atlantic, by contrast, appears to exhibit some predictability. While our analyses focus on combining semiempirical estimates of internal climatic variability with statistical hindcast experiments, possible implications for initialized model predictions are also discussed.

  19. Entropy statistics and information theory

    NARCIS (Netherlands)

    Frenken, K.; Hanusch, H.; Pyka, A.

    2007-01-01

    Entropy measures provide important tools to indicate variety in distributions at particular moments in time (e.g., market shares) and to analyse evolutionary processes over time (e.g., technical change). Importantly, entropy statistics are suitable to decomposition analysis, which renders the

  20. Statistical wave function

    International Nuclear Information System (INIS)

    Levine, R.D.

    1988-01-01

    Statistical considerations are applied to quantum mechanical amplitudes. The physical motivation is the progress in the spectroscopy of highly excited states. The corresponding wave functions are strongly mixed. In terms of a basis set of eigenfunctions of a zeroth-order Hamiltonian with good quantum numbers, such wave functions have contributions from many basis states. The vector x is considered whose components are the expansion coefficients in that basis. Any amplitude can be written as a dagger x x. It is argued that the components of x and hence other amplitudes can be regarded as random variables. The maximum entropy formalism is applied to determine the corresponding distribution function. Two amplitudes a dagger x x and b dagger x x are independently distributed if b dagger x a = 0. It is suggested that the theory of quantal measurements implies that, in general, one can one determine the distribution of amplitudes and not the amplitudes themselves