Statistical analysis in MSW collection performance assessment.
Teixeira, Carlos Afonso; Avelino, Catarina; Ferreira, Fátima; Bentes, Isabel
2014-09-01
The increase of Municipal Solid Waste (MSW) generated over the last years forces waste managers pursuing more effective collection schemes, technically viable, environmentally effective and economically sustainable. The assessment of MSW services using performance indicators plays a crucial role for improving service quality. In this work, we focus on the relevance of regular system monitoring as a service assessment tool. In particular, we select and test a core-set of MSW collection performance indicators (effective collection distance, effective collection time and effective fuel consumption) that highlights collection system strengths and weaknesses and supports pro-active management decision-making and strategic planning. A statistical analysis was conducted with data collected in mixed collection system of Oporto Municipality, Portugal, during one year, a week per month. This analysis provides collection circuits' operational assessment and supports effective short-term municipality collection strategies at the level of, e.g., collection frequency and timetables, and type of containers. Copyright © 2014 Elsevier Ltd. All rights reserved.
Statistical evaluation of diagnostic performance topics in ROC analysis
Zou, Kelly H; Bandos, Andriy I; Ohno-Machado, Lucila; Rockette, Howard E
2016-01-01
Statistical evaluation of diagnostic performance in general and Receiver Operating Characteristic (ROC) analysis in particular are important for assessing the performance of medical tests and statistical classifiers, as well as for evaluating predictive models or algorithms. This book presents innovative approaches in ROC analysis, which are relevant to a wide variety of applications, including medical imaging, cancer research, epidemiology, and bioinformatics. Statistical Evaluation of Diagnostic Performance: Topics in ROC Analysis covers areas including monotone-transformation techniques in parametric ROC analysis, ROC methods for combined and pooled biomarkers, Bayesian hierarchical transformation models, sequential designs and inferences in the ROC setting, predictive modeling, multireader ROC analysis, and free-response ROC (FROC) methodology. The book is suitable for graduate-level students and researchers in statistics, biostatistics, epidemiology, public health, biomedical engineering, radiology, medi...
A Divergence Statistics Extension to VTK for Performance Analysis
Energy Technology Data Exchange (ETDEWEB)
Pebay, Philippe Pierre [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Bennett, Janine Camille [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
2015-02-01
This report follows the series of previous documents ([PT08, BPRT09b, PT09, BPT09, PT10, PB13], where we presented the parallel descriptive, correlative, multi-correlative, principal component analysis, contingency, k -means, order and auto-correlative statistics engines which we developed within the Visualization Tool Kit ( VTK ) as a scalable, parallel and versatile statistics package. We now report on a new engine which we developed for the calculation of divergence statistics, a concept which we hereafter explain and whose main goal is to quantify the discrepancy, in a stasticial manner akin to measuring a distance, between an observed empirical distribution and a theoretical, "ideal" one. The ease of use of the new diverence statistics engine is illustrated by the means of C++ code snippets. Although this new engine does not yet have a parallel implementation, it has already been applied to HPC performance analysis, of which we provide an example.
Statistical analysis of RHIC beam position monitors performance
Calaga, R.; Tomás, R.
2004-04-01
A detailed statistical analysis of beam position monitors (BPM) performance at RHIC is a critical factor in improving regular operations and future runs. Robust identification of malfunctioning BPMs plays an important role in any orbit or turn-by-turn analysis. Singular value decomposition and Fourier transform methods, which have evolved as powerful numerical techniques in signal processing, will aid in such identification from BPM data. This is the first attempt at RHIC to use a large set of data to statistically enhance the capability of these two techniques and determine BPM performance. A comparison from run 2003 data shows striking agreement between the two methods and hence can be used to improve BPM functioning at RHIC and possibly other accelerators.
Statistical analysis of RHIC beam position monitors performance
Directory of Open Access Journals (Sweden)
R. Calaga
2004-04-01
Full Text Available A detailed statistical analysis of beam position monitors (BPM performance at RHIC is a critical factor in improving regular operations and future runs. Robust identification of malfunctioning BPMs plays an important role in any orbit or turn-by-turn analysis. Singular value decomposition and Fourier transform methods, which have evolved as powerful numerical techniques in signal processing, will aid in such identification from BPM data. This is the first attempt at RHIC to use a large set of data to statistically enhance the capability of these two techniques and determine BPM performance. A comparison from run 2003 data shows striking agreement between the two methods and hence can be used to improve BPM functioning at RHIC and possibly other accelerators.
A statistical analysis on the leak detection performance of ...
Indian Academy of Sciences (India)
Chinedu Duru
2017-11-09
Nov 9, 2017 ... of underground and overground pipelines with wireless sensor networks through the .... detection performance analysis of pipeline leakage. This study and ..... case and apply to all materials transported through the pipeline.
Statistical Analysis of EGFR Structures’ Performance in Virtual Screening
Li, Yan; Li, Xiang; Dong, Zigang
2015-01-01
In this work the ability of EGFR structures to distinguish true inhibitors from decoys in docking and MM-PBSA is assessed by statistical procedures. The docking performance depends critically on the receptor conformation and bound state. The enrichment of known inhibitors is well correlated with the difference between EGFR structures rather than the bound-ligand property. The optimal structures for virtual screening can be selected based purely on the complex information. And the mixed combination of distinct EGFR conformations is recommended for ensemble docking. In MM-PBSA, a variety of EGFR structures have identically good performance in the scoring and ranking of known inhibitors, indicating that the choice of the receptor structure has little effect on the screening. PMID:26476847
Statistical Analysis of the Grid Connected Photovoltaic System Performance Ratio
Directory of Open Access Journals (Sweden)
Javier Vilariño-García
2017-05-01
Full Text Available A methodology based on the application of variance analysis and Tukey's method to a data set of solar radiation in the plane of the photovoltaic modules and the corresponding values of power delivered to the grid at intervals of 10 minutes presents from sunrise to sunset during the 52 weeks of the year 2013. These data were obtained through a monitoring system located in a photovoltaic plant of 10 MW of rated power located in Cordoba, consisting of 16 transformers and 98 investors. The application of the comparative method among the middle of the performance index of the processing centers to detect with an analysis of variance if there is significant difference in average at least the rest at a level of significance of 5% and then by testing Tukey which one or more processing centers that are below average due to a fault to be detected and corrected are.
Statistical cluster analysis and diagnosis of nuclear system level performance
International Nuclear Information System (INIS)
Teichmann, T.; Levine, M.M.; Samanta, P.K.; Kato, W.Y.
1985-01-01
The complexity of individual nuclear power plants and the importance of maintaining reliable and safe operations makes it desirable to complement the deterministic analyses of these plants by corresponding statistical surveys and diagnoses. Based on such investigations, one can then explore, statistically, the anticipation, prevention, and when necessary, the control of such failures and malfunctions. This paper, and the accompanying one by Samanta et al., describe some of the initial steps in exploring the feasibility of setting up such a program on an integrated and global (industry-wide) basis. The conceptual statistical and data framework was originally outlined in BNL/NUREG-51609, NUREG/CR-3026, and the present work aims at showing how some important elements might be implemented in a practical way (albeit using hypothetical or simulated data)
Angeler, David G; Viedma, Olga; Moreno, José M
2009-11-01
Time lag analysis (TLA) is a distance-based approach used to study temporal dynamics of ecological communities by measuring community dissimilarity over increasing time lags. Despite its increased use in recent years, its performance in comparison with other more direct methods (i.e., canonical ordination) has not been evaluated. This study fills this gap using extensive simulations and real data sets from experimental temporary ponds (true zooplankton communities) and landscape studies (landscape categories as pseudo-communities) that differ in community structure and anthropogenic stress history. Modeling time with a principal coordinate of neighborhood matrices (PCNM) approach, the canonical ordination technique (redundancy analysis; RDA) consistently outperformed the other statistical tests (i.e., TLAs, Mantel test, and RDA based on linear time trends) using all real data. In addition, the RDA-PCNM revealed different patterns of temporal change, and the strength of each individual time pattern, in terms of adjusted variance explained, could be evaluated, It also identified species contributions to these patterns of temporal change. This additional information is not provided by distance-based methods. The simulation study revealed better Type I error properties of the canonical ordination techniques compared with the distance-based approaches when no deterministic component of change was imposed on the communities. The simulation also revealed that strong emphasis on uniform deterministic change and low variability at other temporal scales is needed to result in decreased statistical power of the RDA-PCNM approach relative to the other methods. Based on the statistical performance of and information content provided by RDA-PCNM models, this technique serves ecologists as a powerful tool for modeling temporal change of ecological (pseudo-) communities.
The statistical analysis techniques to support the NGNP fuel performance experiments
Energy Technology Data Exchange (ETDEWEB)
Pham, Binh T., E-mail: Binh.Pham@inl.gov; Einerson, Jeffrey J.
2013-10-15
This paper describes the development and application of statistical analysis techniques to support the Advanced Gas Reactor (AGR) experimental program on Next Generation Nuclear Plant (NGNP) fuel performance. The experiments conducted in the Idaho National Laboratory’s Advanced Test Reactor employ fuel compacts placed in a graphite cylinder shrouded by a steel capsule. The tests are instrumented with thermocouples embedded in graphite blocks and the target quantity (fuel temperature) is regulated by the He–Ne gas mixture that fills the gap volume. Three techniques for statistical analysis, namely control charting, correlation analysis, and regression analysis, are implemented in the NGNP Data Management and Analysis System for automated processing and qualification of the AGR measured data. The neutronic and thermal code simulation results are used for comparative scrutiny. The ultimate objective of this work includes (a) a multi-faceted system for data monitoring and data accuracy testing, (b) identification of possible modes of diagnostics deterioration and changes in experimental conditions, (c) qualification of data for use in code validation, and (d) identification and use of data trends to support effective control of test conditions with respect to the test target. Analysis results and examples given in the paper show the three statistical analysis techniques providing a complementary capability to warn of thermocouple failures. It also suggests that the regression analysis models relating calculated fuel temperatures and thermocouple readings can enable online regulation of experimental parameters (i.e. gas mixture content), to effectively maintain the fuel temperature within a given range.
A knowledge-based T2-statistic to perform pathway analysis for quantitative proteomic data.
Lai, En-Yu; Chen, Yi-Hau; Wu, Kun-Pin
2017-06-01
Approaches to identify significant pathways from high-throughput quantitative data have been developed in recent years. Still, the analysis of proteomic data stays difficult because of limited sample size. This limitation also leads to the practice of using a competitive null as common approach; which fundamentally implies genes or proteins as independent units. The independent assumption ignores the associations among biomolecules with similar functions or cellular localization, as well as the interactions among them manifested as changes in expression ratios. Consequently, these methods often underestimate the associations among biomolecules and cause false positives in practice. Some studies incorporate the sample covariance matrix into the calculation to address this issue. However, sample covariance may not be a precise estimation if the sample size is very limited, which is usually the case for the data produced by mass spectrometry. In this study, we introduce a multivariate test under a self-contained null to perform pathway analysis for quantitative proteomic data. The covariance matrix used in the test statistic is constructed by the confidence scores retrieved from the STRING database or the HitPredict database. We also design an integrating procedure to retain pathways of sufficient evidence as a pathway group. The performance of the proposed T2-statistic is demonstrated using five published experimental datasets: the T-cell activation, the cAMP/PKA signaling, the myoblast differentiation, and the effect of dasatinib on the BCR-ABL pathway are proteomic datasets produced by mass spectrometry; and the protective effect of myocilin via the MAPK signaling pathway is a gene expression dataset of limited sample size. Compared with other popular statistics, the proposed T2-statistic yields more accurate descriptions in agreement with the discussion of the original publication. We implemented the T2-statistic into an R package T2GA, which is available at https
The Statistical Analysis Techniques to Support the NGNP Fuel Performance Experiments
International Nuclear Information System (INIS)
Pham, Bihn T.; Einerson, Jeffrey J.
2010-01-01
This paper describes the development and application of statistical analysis techniques to support the AGR experimental program on NGNP fuel performance. The experiments conducted in the Idaho National Laboratory's Advanced Test Reactor employ fuel compacts placed in a graphite cylinder shrouded by a steel capsule. The tests are instrumented with thermocouples embedded in graphite blocks and the target quantity (fuel/graphite temperature) is regulated by the He-Ne gas mixture that fills the gap volume. Three techniques for statistical analysis, namely control charting, correlation analysis, and regression analysis, are implemented in the SAS-based NGNP Data Management and Analysis System (NDMAS) for automated processing and qualification of the AGR measured data. The NDMAS also stores daily neutronic (power) and thermal (heat transfer) code simulation results along with the measurement data, allowing for their combined use and comparative scrutiny. The ultimate objective of this work includes (a) a multi-faceted system for data monitoring and data accuracy testing, (b) identification of possible modes of diagnostics deterioration and changes in experimental conditions, (c) qualification of data for use in code validation, and (d) identification and use of data trends to support effective control of test conditions with respect to the test target. Analysis results and examples given in the paper show the three statistical analysis techniques providing a complementary capability to warn of thermocouple failures. It also suggests that the regression analysis models relating calculated fuel temperatures and thermocouple readings can enable online regulation of experimental parameters (i.e. gas mixture content), to effectively maintain the target quantity (fuel temperature) within a given range.
International Nuclear Information System (INIS)
Hofland, G.S.; Barton, C.C.
1990-01-01
The computer program FREQFIT is designed to perform regression and statistical chi-squared goodness of fit analysis on one-dimensional or two-dimensional data. The program features an interactive user dialogue, numerous help messages, an option for screen or line printer output, and the flexibility to use practically any commercially available graphics package to create plots of the program's results. FREQFIT is written in Microsoft QuickBASIC, for IBM-PC compatible computers. A listing of the QuickBASIC source code for the FREQFIT program, a user manual, and sample input data, output, and plots are included. 6 refs., 1 fig
Huang, Erich P; Wang, Xiao-Feng; Choudhury, Kingshuk Roy; McShane, Lisa M; Gönen, Mithat; Ye, Jingjing; Buckler, Andrew J; Kinahan, Paul E; Reeves, Anthony P; Jackson, Edward F; Guimaraes, Alexander R; Zahlmann, Gudrun
2015-02-01
Medical imaging serves many roles in patient care and the drug approval process, including assessing treatment response and guiding treatment decisions. These roles often involve a quantitative imaging biomarker, an objectively measured characteristic of the underlying anatomic structure or biochemical process derived from medical images. Before a quantitative imaging biomarker is accepted for use in such roles, the imaging procedure to acquire it must undergo evaluation of its technical performance, which entails assessment of performance metrics such as repeatability and reproducibility of the quantitative imaging biomarker. Ideally, this evaluation will involve quantitative summaries of results from multiple studies to overcome limitations due to the typically small sample sizes of technical performance studies and/or to include a broader range of clinical settings and patient populations. This paper is a review of meta-analysis procedures for such an evaluation, including identification of suitable studies, statistical methodology to evaluate and summarize the performance metrics, and complete and transparent reporting of the results. This review addresses challenges typical of meta-analyses of technical performance, particularly small study sizes, which often causes violations of assumptions underlying standard meta-analysis techniques. Alternative approaches to address these difficulties are also presented; simulation studies indicate that they outperform standard techniques when some studies are small. The meta-analysis procedures presented are also applied to actual [18F]-fluorodeoxyglucose positron emission tomography (FDG-PET) test-retest repeatability data for illustrative purposes. © The Author(s) 2014 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.
McSharry, Patrick E
2007-12-22
To assess the effect of altitude on match results and physiological performance of a large and diverse population of professional athletes. Statistical analysis of international football (soccer) scores and results. FIFA extensive database of 1460 football matches in 10 countries spanning over 100 years. Altitude had a significant (Pnegative impact on physiological performance as revealed through the overall underperformance of low altitude teams when playing against high altitude teams in South America. High altitude teams score more and concede fewer goals with increasing altitude difference. Each additional 1000 m of altitude difference increases the goal difference by about half of a goal. The probability of the home team winning for two teams from the same altitude is 0.537, whereas this rises to 0.825 for a home team with an altitude difference of 3695 m (such as Bolivia v Brazil) and falls to 0.213 when the altitude difference is -3695 m (such as Brazil v Bolivia). Altitude provides a significant advantage for high altitude teams when playing international football games at both low and high altitudes. Lowland teams are unable to acclimatise to high altitude, reducing physiological performance. As physiological performance does not protect against the effect of altitude, better predictors of individual susceptibility to altitude illness would facilitate team selection.
U.S. Department of Health & Human Services — This section contains statistical information and reports related to the percentage of electronic transactions being sent to Medicare contractors in the formats...
Statistical data analysis handbook
National Research Council Canada - National Science Library
Wall, Francis J
1986-01-01
It must be emphasized that this is not a text book on statistics. Instead it is a working tool that presents data analysis in clear, concise terms which can be readily understood even by those without formal training in statistics...
A study of the feasibility of statistical analysis of airport performance simulation
Myers, R. H.
1982-01-01
The feasibility of conducting a statistical analysis of simulation experiments to study airport capacity is investigated. First, the form of the distribution of airport capacity is studied. Since the distribution is non-Gaussian, it is important to determine the effect of this distribution on standard analysis of variance techniques and power calculations. Next, power computations are made in order to determine how economic simulation experiments would be if they are designed to detect capacity changes from condition to condition. Many of the conclusions drawn are results of Monte-Carlo techniques.
Directory of Open Access Journals (Sweden)
Kępniak M.
2016-12-01
Full Text Available This paper addresses the tensile and flexural strength of HPC (high performance concrete. The aim of the paper is to analyse the efficiency of models proposed in different codes. In particular, three design procedures from: the ACI 318 [1], Eurocode 2 [2] and the Model Code 2010 [3] are considered. The associations between design tensile strength of concrete obtained from these three codes and compressive strength are compared with experimental results of tensile strength and flexural strength by statistical tools. Experimental results of tensile strength were obtained in the splitting test. Based on this comparison, conclusions are drawn according to the fit between the design methods and the test data. The comparison shows that tensile strength and flexural strength of HPC depend on more influential factors and not only compressive strength.
Chen, Tsung-Tai; Chang, Yun-Jau; Ku, Shei-Ling; Chung, Kuo-Piao
2010-10-01
There is much research using statistical process control (SPC) to monitor surgical performance, including comparisons among groups to detect small process shifts, but few of these studies have included a stabilization process. This study aimed to analyse the performance of surgeons in operating room (OR) and set a benchmark by SPC after stabilized process. The OR profile of 499 patients who underwent laparoscopic cholecystectomy performed by 16 surgeons at a tertiary hospital in Taiwan during 2005 and 2006 were recorded. SPC was applied to analyse operative and non-operative times using the following five steps: first, the times were divided into two segments; second, they were normalized; third, they were evaluated as individual processes; fourth, the ARL(0) was calculated;, and fifth, the different groups (surgeons) were compared. Outliers were excluded to ensure stability for each group and to facilitate inter-group comparison. The results showed that in the stabilized process, only one surgeon exhibited a significantly shorter total process time (including operative time and non-operative time). In this study, we use five steps to demonstrate how to control surgical and non-surgical time in phase I. There are some measures that can be taken to prevent skew and instability in the process. Also, using SPC, one surgeon can be shown to be a real benchmark. © 2010 Blackwell Publishing Ltd.
Li, Y.; Kirchengast, G.; Scherllin-Pirscher, B.; Norman, R.; Yuan, Y. B.; Fritzer, J.; Schwaerz, M.; Zhang, K.
2015-08-01
We introduce a new dynamic statistical optimization algorithm to initialize ionosphere-corrected bending angles of Global Navigation Satellite System (GNSS)-based radio occultation (RO) measurements. The new algorithm estimates background and observation error covariance matrices with geographically varying uncertainty profiles and realistic global-mean correlation matrices. The error covariance matrices estimated by the new approach are more accurate and realistic than in simplified existing approaches and can therefore be used in statistical optimization to provide optimal bending angle profiles for high-altitude initialization of the subsequent Abel transform retrieval of refractivity. The new algorithm is evaluated against the existing Wegener Center Occultation Processing System version 5.6 (OPSv5.6) algorithm, using simulated data on two test days from January and July 2008 and real observed CHAllenging Minisatellite Payload (CHAMP) and Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) measurements from the complete months of January and July 2008. The following is achieved for the new method's performance compared to OPSv5.6: (1) significant reduction of random errors (standard deviations) of optimized bending angles down to about half of their size or more; (2) reduction of the systematic differences in optimized bending angles for simulated MetOp data; (3) improved retrieval of refractivity and temperature profiles; and (4) realistically estimated global-mean correlation matrices and realistic uncertainty fields for the background and observations. Overall the results indicate high suitability for employing the new dynamic approach in the processing of long-term RO data into a reference climate record, leading to well-characterized and high-quality atmospheric profiles over the entire stratosphere.
Beginning statistics with data analysis
Mosteller, Frederick; Rourke, Robert EK
2013-01-01
This introduction to the world of statistics covers exploratory data analysis, methods for collecting data, formal statistical inference, and techniques of regression and analysis of variance. 1983 edition.
Directory of Open Access Journals (Sweden)
John R. Speakman
2013-03-01
Full Text Available The epidemics of obesity and diabetes have aroused great interest in the analysis of energy balance, with the use of organisms ranging from nematode worms to humans. Although generating energy-intake or -expenditure data is relatively straightforward, the most appropriate way to analyse the data has been an issue of contention for many decades. In the last few years, a consensus has been reached regarding the best methods for analysing such data. To facilitate using these best-practice methods, we present here an algorithm that provides a step-by-step guide for analysing energy-intake or -expenditure data. The algorithm can be used to analyse data from either humans or experimental animals, such as small mammals or invertebrates. It can be used in combination with any commercial statistics package; however, to assist with analysis, we have included detailed instructions for performing each step for three popular statistics packages (SPSS, MINITAB and R. We also provide interpretations of the results obtained at each step. We hope that this algorithm will assist in the statistically appropriate analysis of such data, a field in which there has been much confusion and some controversy.
Fouladi, Rachel T.
2000-01-01
Provides an overview of standard and modified normal theory and asymptotically distribution-free covariance and correlation structure analysis techniques and details Monte Carlo simulation results on Type I and Type II error control. Demonstrates through the simulation that robustness and nonrobustness of structure analysis techniques vary as a…
Applied multivariate statistical analysis
Härdle, Wolfgang Karl
2015-01-01
Focusing on high-dimensional applications, this 4th edition presents the tools and concepts used in multivariate data analysis in a style that is also accessible for non-mathematicians and practitioners. It surveys the basic principles and emphasizes both exploratory and inferential statistics; a new chapter on Variable Selection (Lasso, SCAD and Elastic Net) has also been added. All chapters include practical exercises that highlight applications in different multivariate data analysis fields: in quantitative financial studies, where the joint dynamics of assets are observed; in medicine, where recorded observations of subjects in different locations form the basis for reliable diagnoses and medication; and in quantitative marketing, where consumers’ preferences are collected in order to construct models of consumer behavior. All of these examples involve high to ultra-high dimensions and represent a number of major fields in big data analysis. The fourth edition of this book on Applied Multivariate ...
Performances of non-parametric statistics in sensitivity analysis and parameter ranking
International Nuclear Information System (INIS)
Saltelli, A.
1987-01-01
Twelve parametric and non-parametric sensitivity analysis techniques are compared in the case of non-linear model responses. The test models used are taken from the long-term risk analysis for the disposal of high level radioactive waste in a geological formation. They describe the transport of radionuclides through a set of engineered and natural barriers from the repository to the biosphere and to man. The output data from these models are the dose rates affecting the maximum exposed individual of a critical group at a given point in time. All the techniques are applied to the output from the same Monte Carlo simulations, where a modified version of Latin Hypercube method is used for the sample selection. Hypothesis testing is systematically applied to quantify the degree of confidence in the results given by the various sensitivity estimators. The estimators are ranked according to their robustness and stability, on the basis of two test cases. The conclusions are that no estimator can be considered the best from all points of view and recommend the use of more than just one estimator in sensitivity analysis
Closed loop statistical performance analysis of N-K knock controllers
Peyton Jones, James C.; Shayestehmanesh, Saeed; Frey, Jesse
2017-09-01
The closed loop performance of engine knock controllers cannot be rigorously assessed from single experiments or simulations because knock behaves as a random process and therefore the response belongs to a random distribution also. In this work a new method is proposed for computing the distributions and expected values of the closed loop response, both in steady state and in response to disturbances. The method takes as its input the control law, and the knock propensity characteristic of the engine which is mapped from open loop steady state tests. The method is applicable to the 'n-k' class of knock controllers in which the control action is a function only of the number of cycles n since the last control move, and the number k of knock events that have occurred in this time. A Cumulative Summation (CumSum) based controller falls within this category, and the method is used to investigate the performance of the controller in a deeper and more rigorous way than has previously been possible. The results are validated using onerous Monte Carlo simulations, which confirm both the validity of the method and its high computational efficiency.
Directory of Open Access Journals (Sweden)
Haejoon Jung
2018-01-01
Full Text Available As an intrinsic part of the Internet of Things (IoT ecosystem, machine-to-machine (M2M communications are expected to provide ubiquitous connectivity between machines. Millimeter-wave (mmWave communication is another promising technology for the future communication systems to alleviate the pressure of scarce spectrum resources. For this reason, in this paper, we consider multi-hop M2M communications, where a machine-type communication (MTC device with the limited transmit power relays to help other devices using mmWave. To be specific, we focus on hop distance statistics and their impacts on system performances in multi-hop wireless networks (MWNs with directional antenna arrays in mmWave for M2M communications. Different from microwave systems, in mmWave communications, wireless channel suffers from blockage by obstacles that heavily attenuate line-of-sight signals, which may result in limited per-hop progress in MWNs. We consider two routing strategies aiming at different types of applications and derive the probability distributions of their hop distances. Moreover, we provide their baseline statistics assuming the blockage-free scenario to quantify the impact of blockages. Based on the hop distance analysis, we propose a method to estimate the end-to-end performances (e.g., outage probability, hop count, and transmit energy of the mmWave MWNs, which provides important insights into mmWave MWN design without time-consuming and repetitive end-to-end simulation.
Jung, Haejoon; Lee, In-Ho
2018-01-12
As an intrinsic part of the Internet of Things (IoT) ecosystem, machine-to-machine (M2M) communications are expected to provide ubiquitous connectivity between machines. Millimeter-wave (mmWave) communication is another promising technology for the future communication systems to alleviate the pressure of scarce spectrum resources. For this reason, in this paper, we consider multi-hop M2M communications, where a machine-type communication (MTC) device with the limited transmit power relays to help other devices using mmWave. To be specific, we focus on hop distance statistics and their impacts on system performances in multi-hop wireless networks (MWNs) with directional antenna arrays in mmWave for M2M communications. Different from microwave systems, in mmWave communications, wireless channel suffers from blockage by obstacles that heavily attenuate line-of-sight signals, which may result in limited per-hop progress in MWNs. We consider two routing strategies aiming at different types of applications and derive the probability distributions of their hop distances. Moreover, we provide their baseline statistics assuming the blockage-free scenario to quantify the impact of blockages. Based on the hop distance analysis, we propose a method to estimate the end-to-end performances (e.g., outage probability, hop count, and transmit energy) of the mmWave MWNs, which provides important insights into mmWave MWN design without time-consuming and repetitive end-to-end simulation.
International Nuclear Information System (INIS)
Yamaoka, Naoto; Watanabe, Wataru; Hontani, Hidekata
2010-01-01
Most of the time when we construct statistical point cloud model, we need to calculate the corresponding points. Constructed statistical model will not be the same if we use different types of method to calculate the corresponding points. This article proposes the effect to statistical model of human organ made by different types of method to calculate the corresponding points. We validated the performance of statistical model by registering a surface of an organ in a 3D medical image. We compare two methods to calculate corresponding points. The first, the 'Generalized Multi-Dimensional Scaling (GMDS)', determines the corresponding points by the shapes of two curved surfaces. The second approach, the 'Entropy-based Particle system', chooses corresponding points by calculating a number of curved surfaces statistically. By these methods we construct the statistical models and using these models we conducted registration with the medical image. For the estimation, we use non-parametric belief propagation and this method estimates not only the position of the organ but also the probability density of the organ position. We evaluate how the two different types of method that calculates corresponding points affects the statistical model by change in probability density of each points. (author)
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...
Statistical Analysis and validation
Hoefsloot, H.C.J.; Horvatovich, P.; Bischoff, R.
2013-01-01
In this chapter guidelines are given for the selection of a few biomarker candidates from a large number of compounds with a relative low number of samples. The main concepts concerning the statistical validation of the search for biomarkers are discussed. These complicated methods and concepts are
International Nuclear Information System (INIS)
Hahn, A.A.
1994-11-01
The complexity of instrumentation sometimes requires data analysis to be done before the result is presented to the control room. This tutorial reviews some of the theoretical assumptions underlying the more popular forms of data analysis and presents simple examples to illuminate the advantages and hazards of different techniques
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.
DEFF Research Database (Denmark)
Ris Hansen, Inge; Søgaard, Karen; Gram, Bibi
2015-01-01
This is the analysis plan for the multicentre randomised control study looking at the effect of training and exercises in chronic neck pain patients that is being conducted in Jutland and Funen, Denmark. This plan will be used as a work description for the analyses of the data collected....
Statistical Power in Meta-Analysis
Liu, Jin
2015-01-01
Statistical power is important in a meta-analysis study, although few studies have examined the performance of simulated power in meta-analysis. The purpose of this study is to inform researchers about statistical power estimation on two sample mean difference test under different situations: (1) the discrepancy between the analytical power and…
International Nuclear Information System (INIS)
2008-05-01
This book introduces energy and resource technology development business with performance analysis, which has business division and definition, analysis of current situation of support, substance of basic plan of national energy, resource technique development, selection of analysis index, result of performance analysis by index, performance result of investigation, analysis and appraisal of energy and resource technology development business in 2007.
Research design and statistical analysis
Myers, Jerome L; Lorch Jr, Robert F
2013-01-01
Research Design and Statistical Analysis provides comprehensive coverage of the design principles and statistical concepts necessary to make sense of real data. The book's goal is to provide a strong conceptual foundation to enable readers to generalize concepts to new research situations. Emphasis is placed on the underlying logic and assumptions of the analysis and what it tells the researcher, the limitations of the analysis, and the consequences of violating assumptions. Sampling, design efficiency, and statistical models are emphasized throughout. As per APA recommendations
Snell, Kym Ie; Ensor, Joie; Debray, Thomas Pa; Moons, Karel Gm; Riley, Richard D
2017-01-01
If individual participant data are available from multiple studies or clusters, then a prediction model can be externally validated multiple times. This allows the model's discrimination and calibration performance to be examined across different settings. Random-effects meta-analysis can then be used to quantify overall (average) performance and heterogeneity in performance. This typically assumes a normal distribution of 'true' performance across studies. We conducted a simulation study to examine this normality assumption for various performance measures relating to a logistic regression prediction model. We simulated data across multiple studies with varying degrees of variability in baseline risk or predictor effects and then evaluated the shape of the between-study distribution in the C-statistic, calibration slope, calibration-in-the-large, and E/O statistic, and possible transformations thereof. We found that a normal between-study distribution was usually reasonable for the calibration slope and calibration-in-the-large; however, the distributions of the C-statistic and E/O were often skewed across studies, particularly in settings with large variability in the predictor effects. Normality was vastly improved when using the logit transformation for the C-statistic and the log transformation for E/O, and therefore we recommend these scales to be used for meta-analysis. An illustrated example is given using a random-effects meta-analysis of the performance of QRISK2 across 25 general practices.
Performance modeling, stochastic networks, and statistical multiplexing
Mazumdar, Ravi R
2013-01-01
This monograph presents a concise mathematical approach for modeling and analyzing the performance of communication networks with the aim of introducing an appropriate mathematical framework for modeling and analysis as well as understanding the phenomenon of statistical multiplexing. The models, techniques, and results presented form the core of traffic engineering methods used to design, control and allocate resources in communication networks.The novelty of the monograph is the fresh approach and insights provided by a sample-path methodology for queueing models that highlights the importan
Regularized Statistical Analysis of Anatomy
DEFF Research Database (Denmark)
Sjöstrand, Karl
2007-01-01
This thesis presents the application and development of regularized methods for the statistical analysis of anatomical structures. Focus is on structure-function relationships in the human brain, such as the connection between early onset of Alzheimer’s disease and shape changes of the corpus...... and mind. Statistics represents a quintessential part of such investigations as they are preluded by a clinical hypothesis that must be verified based on observed data. The massive amounts of image data produced in each examination pose an important and interesting statistical challenge...... efficient algorithms which make the analysis of large data sets feasible, and gives examples of applications....
Comparative Gender Performance in Business Statistics.
Mogull, Robert G.
1989-01-01
Comparative performance of male and female students in introductory and intermediate statistics classes was examined for over 16 years at a state university. Gender means from 97 classes and 1,609 males and 1,085 females revealed a probabilistic--although statistically insignificant--superior performance by female students that appeared to…
Directory of Open Access Journals (Sweden)
Pierluigi Perrone
2017-01-01
Full Text Available Transmission demand continues to grow and higher capacity optical communication systems are required to economically meet this ever-increasing need for communication services. This article expands and deepens the study of a novel optical communication system for high-capacity Local Area Networks (LANs, based on twisted optical fibers. The complete statistical behavior of this system is shown, designed for more efficient use of the fiber single-channel capacity by adopting an unconventional multilevel polarization modulation (called “bands of polarization”. Starting from simulative results, a possible reference mathematical model is proposed. Finally, the system performance is analyzed in the presence of shot-noise (coherent detection or thermal noise (direct detection.
Haagmans, G. G.; Verhagen, S.; Voûte, R. L.; Verbree, E.
2017-09-01
Since GPS tends to fail for indoor positioning purposes, alternative methods like indoor positioning systems (IPS) based on Bluetooth low energy (BLE) are developing rapidly. Generally, IPS are deployed in environments covered with obstacles such as furniture, walls, people and electronics influencing the signal propagation. The major factor influencing the system performance and to acquire optimal positioning results is the geometry of the beacons. The geometry of the beacons is limited to the available infrastructure that can be deployed (number of beacons, basestations and tags), which leads to the following challenge: Given a limited number of beacons, where should they be placed in a specified indoor environment, such that the geometry contributes to optimal positioning results? This paper aims to propose a statistical model that is able to select the optimal configuration that satisfies the user requirements in terms of precision. The model requires the definition of a chosen 3D space (in our case 7 × 10 × 6 meter), number of beacons, possible user tag locations and a performance threshold (e.g. required precision). For any given set of beacon and receiver locations, the precision, internal- and external reliability can be determined on forehand. As validation, the modeled precision has been compared with observed precision results. The measurements have been performed with an IPS of BlooLoc at a chosen set of user tag locations for a given geometric configuration. Eventually, the model is able to select the optimal geometric configuration out of millions of possible configurations based on a performance threshold (e.g. required precision).
A statistical model for predicting muscle performance
Byerly, Diane Leslie De Caix
The objective of these studies was to develop a capability for predicting muscle performance and fatigue to be utilized for both space- and ground-based applications. To develop this predictive model, healthy test subjects performed a defined, repetitive dynamic exercise to failure using a Lordex spinal machine. Throughout the exercise, surface electromyography (SEMG) data were collected from the erector spinae using a Mega Electronics ME3000 muscle tester and surface electrodes placed on both sides of the back muscle. These data were analyzed using a 5th order Autoregressive (AR) model and statistical regression analysis. It was determined that an AR derived parameter, the mean average magnitude of AR poles, significantly correlated with the maximum number of repetitions (designated Rmax) that a test subject was able to perform. Using the mean average magnitude of AR poles, a test subject's performance to failure could be predicted as early as the sixth repetition of the exercise. This predictive model has the potential to provide a basis for improving post-space flight recovery, monitoring muscle atrophy in astronauts and assessing the effectiveness of countermeasures, monitoring astronaut performance and fatigue during Extravehicular Activity (EVA) operations, providing pre-flight assessment of the ability of an EVA crewmember to perform a given task, improving the design of training protocols and simulations for strenuous International Space Station assembly EVA, and enabling EVA work task sequences to be planned enhancing astronaut performance and safety. Potential ground-based, medical applications of the predictive model include monitoring muscle deterioration and performance resulting from illness, establishing safety guidelines in the industry for repetitive tasks, monitoring the stages of rehabilitation for muscle-related injuries sustained in sports and accidents, and enhancing athletic performance through improved training protocols while reducing
Statistical learning methods: Basics, control and performance
Energy Technology Data Exchange (ETDEWEB)
Zimmermann, J. [Max-Planck-Institut fuer Physik, Foehringer Ring 6, 80805 Munich (Germany)]. E-mail: zimmerm@mppmu.mpg.de
2006-04-01
The basics of statistical learning are reviewed with a special emphasis on general principles and problems for all different types of learning methods. Different aspects of controlling these methods in a physically adequate way will be discussed. All principles and guidelines will be exercised on examples for statistical learning methods in high energy and astrophysics. These examples prove in addition that statistical learning methods very often lead to a remarkable performance gain compared to the competing classical algorithms.
Statistical learning methods: Basics, control and performance
International Nuclear Information System (INIS)
Zimmermann, J.
2006-01-01
The basics of statistical learning are reviewed with a special emphasis on general principles and problems for all different types of learning methods. Different aspects of controlling these methods in a physically adequate way will be discussed. All principles and guidelines will be exercised on examples for statistical learning methods in high energy and astrophysics. These examples prove in addition that statistical learning methods very often lead to a remarkable performance gain compared to the competing classical algorithms
Directory of Open Access Journals (Sweden)
H. Zareabyaneh
2014-12-01
Full Text Available Any planning for the future requires estimates of future conditions. It is possible to study changes over time series. In this study, changes of production and cultivated area of 17 field crops of Khorasan Razavi province in a 25-year period were determined with Mann - Kendall test, Sen’s Estimator Slope and linear regression. Analysis of the three tests showed that performance of 76.5% from yield, 88.2% from area under cultivation and 55.8% from agricultural production were significant at the 0.01 and 0.05 level. On the other hand, trend of yields 58.8% was increase, 17.7% was reduced and 23.5% was no significant trend. Similarly, trend of 23.5% from area under cultivation was acreage, 64.7% was reduction, and 11.8% was no significant trend. For production variable, 29.4% was significantly increased and 29.4% was significant reduction. More detailed analysis showed that performance, production and area under cultivation of three crops of cotton, grain and tomatoes increased significantly. Results of all three methods showed the highest trend of negatively performance and area under cultivation variation is related to pea and melon respectively. Furthermore, most of the positive trend in production of tomatoes and grain, performance in onions, potatoes and tomatoes and area under cultivation in tomato observed. The results showed that linear trend and the nonparametric tests of important products of province: wheat, barley, sugar beet, cotton, melons, watermelons and tomatoes in 0.01 were significant. This result shows the importance of these yields in gross state province product.
Bayesian Inference in Statistical Analysis
Box, George E P
2011-01-01
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 Rob
The statistical analysis of anisotropies
International Nuclear Information System (INIS)
Webster, A.
1977-01-01
One of the many uses to which a radio survey may be put is an analysis of the distribution of the radio sources on the celestial sphere to find out whether they are bunched into clusters or lie in preferred regions of space. There are many methods of testing for clustering in point processes and since they are not all equally good this contribution is presented as a brief guide to what seems to be the best of them. The radio sources certainly do not show very strong clusering and may well be entirely unclustered so if a statistical method is to be useful it must be both powerful and flexible. A statistic is powerful in this context if it can efficiently distinguish a weakly clustered distribution of sources from an unclustered one, and it is flexible if it can be applied in a way which avoids mistaking defects in the survey for true peculiarities in the distribution of sources. The paper divides clustering statistics into two classes: number density statistics and log N/log S statistics. (Auth.)
Statistical evaluation of vibration analysis techniques
Milner, G. Martin; Miller, Patrice S.
1987-01-01
An evaluation methodology is presented for a selection of candidate vibration analysis techniques applicable to machinery representative of the environmental control and life support system of advanced spacecraft; illustrative results are given. Attention is given to the statistical analysis of small sample experiments, the quantification of detection performance for diverse techniques through the computation of probability of detection versus probability of false alarm, and the quantification of diagnostic performance.
Statistical analysis of environmental data
International Nuclear Information System (INIS)
Beauchamp, J.J.; Bowman, K.O.; Miller, F.L. Jr.
1975-10-01
This report summarizes the analyses of data obtained by the Radiological Hygiene Branch of the Tennessee Valley Authority from samples taken around the Browns Ferry Nuclear Plant located in Northern Alabama. The data collection was begun in 1968 and a wide variety of types of samples have been gathered on a regular basis. The statistical analysis of environmental data involving very low-levels of radioactivity is discussed. Applications of computer calculations for data processing are described
Performance modeling, loss networks, and statistical multiplexing
Mazumdar, Ravi
2009-01-01
This monograph presents a concise mathematical approach for modeling and analyzing the performance of communication networks with the aim of understanding the phenomenon of statistical multiplexing. The novelty of the monograph is the fresh approach and insights provided by a sample-path methodology for queueing models that highlights the important ideas of Palm distributions associated with traffic models and their role in performance measures. Also presented are recent ideas of large buffer, and many sources asymptotics that play an important role in understanding statistical multiplexing. I
Statistical considerations on safety analysis
International Nuclear Information System (INIS)
Pal, L.; Makai, M.
2004-01-01
The authors have investigated the statistical methods applied to safety analysis of nuclear reactors and arrived at alarming conclusions: a series of calculations with the generally appreciated safety code ATHLET were carried out to ascertain the stability of the results against input uncertainties in a simple experimental situation. Scrutinizing those calculations, we came to the conclusion that the ATHLET results may exhibit chaotic behavior. A further conclusion is that the technological limits are incorrectly set when the output variables are correlated. Another formerly unnoticed conclusion of the previous ATHLET calculations that certain innocent looking parameters (like wall roughness factor, the number of bubbles per unit volume, the number of droplets per unit volume) can influence considerably such output parameters as water levels. The authors are concerned with the statistical foundation of present day safety analysis practices and can only hope that their own misjudgment will be dispelled. Until then, the authors suggest applying correct statistical methods in safety analysis even if it makes the analysis more expensive. It would be desirable to continue exploring the role of internal parameters (wall roughness factor, steam-water surface in thermal hydraulics codes, homogenization methods in neutronics codes) in system safety codes and to study their effects on the analysis. In the validation and verification process of a code one carries out a series of computations. The input data are not precisely determined because measured data have an error, calculated data are often obtained from a more or less accurate model. Some users of large codes are content with comparing the nominal output obtained from the nominal input, whereas all the possible inputs should be taken into account when judging safety. At the same time, any statement concerning safety must be aleatory, and its merit can be judged only when the probability is known with which the
Performing Inferential Statistics Prior to Data Collection
Trafimow, David; MacDonald, Justin A.
2017-01-01
Typically, in education and psychology research, the investigator collects data and subsequently performs descriptive and inferential statistics. For example, a researcher might compute group means and use the null hypothesis significance testing procedure to draw conclusions about the populations from which the groups were drawn. We propose an…
Statistical analysis of JET disruptions
International Nuclear Information System (INIS)
Tanga, A.; Johnson, M.F.
1991-07-01
In the operation of JET and of any tokamak many discharges are terminated by a major disruption. The disruptive termination of a discharge is usually an unwanted event which may cause damage to the structure of the vessel. In a reactor disruptions are potentially a very serious problem, hence the importance of studying them and devising methods to avoid disruptions. Statistical information has been collected about the disruptions which have occurred at JET over a long span of operations. The analysis is focused on the operational aspects of the disruptions rather than on the underlining physics. (Author)
Statistical Analysis of Protein Ensembles
Máté, Gabriell; Heermann, Dieter
2014-04-01
As 3D protein-configuration data is piling up, there is an ever-increasing need for well-defined, mathematically rigorous analysis approaches, especially that the vast majority of the currently available methods rely heavily on heuristics. We propose an analysis framework which stems from topology, the field of mathematics which studies properties preserved under continuous deformations. First, we calculate a barcode representation of the molecules employing computational topology algorithms. Bars in this barcode represent different topological features. Molecules are compared through their barcodes by statistically determining the difference in the set of their topological features. As a proof-of-principle application, we analyze a dataset compiled of ensembles of different proteins, obtained from the Ensemble Protein Database. We demonstrate that our approach correctly detects the different protein groupings.
Statistical data analysis using SAS intermediate statistical methods
Marasinghe, Mervyn G
2018-01-01
The aim of this textbook (previously titled SAS for Data Analytics) is to teach the use of SAS for statistical analysis of data for advanced undergraduate and graduate students in statistics, data science, and disciplines involving analyzing data. The book begins with an introduction beyond the basics of SAS, illustrated with non-trivial, real-world, worked examples. It proceeds to SAS programming and applications, SAS graphics, statistical analysis of regression models, analysis of variance models, analysis of variance with random and mixed effects models, and then takes the discussion beyond regression and analysis of variance to conclude. Pedagogically, the authors introduce theory and methodological basis topic by topic, present a problem as an application, followed by a SAS analysis of the data provided and a discussion of results. The text focuses on applied statistical problems and methods. Key features include: end of chapter exercises, downloadable SAS code and data sets, and advanced material suitab...
Imaging mass spectrometry statistical analysis.
Jones, Emrys A; Deininger, Sören-Oliver; Hogendoorn, Pancras C W; Deelder, André M; McDonnell, Liam A
2012-08-30
Imaging mass spectrometry is increasingly used to identify new candidate biomarkers. This clinical application of imaging mass spectrometry is highly multidisciplinary: expertise in mass spectrometry is necessary to acquire high quality data, histology is required to accurately label the origin of each pixel's mass spectrum, disease biology is necessary to understand the potential meaning of the imaging mass spectrometry results, and statistics to assess the confidence of any findings. Imaging mass spectrometry data analysis is further complicated because of the unique nature of the data (within the mass spectrometry field); several of the assumptions implicit in the analysis of LC-MS/profiling datasets are not applicable to imaging. The very large size of imaging datasets and the reporting of many data analysis routines, combined with inadequate training and accessible reviews, have exacerbated this problem. In this paper we provide an accessible review of the nature of imaging data and the different strategies by which the data may be analyzed. Particular attention is paid to the assumptions of the data analysis routines to ensure that the reader is apprised of their correct usage in imaging mass spectrometry research. Copyright © 2012 Elsevier B.V. All rights reserved.
Parametric statistical change point analysis
Chen, Jie
2000-01-01
This work is an in-depth study of the change point problem from a general point of view and a further examination of change point analysis of the most commonly used statistical models Change point problems are encountered in such disciplines as economics, finance, medicine, psychology, signal processing, and geology, to mention only several The exposition is clear and systematic, with a great deal of introductory material included Different models are presented in each chapter, including gamma and exponential models, rarely examined thus far in the literature Other models covered in detail are the multivariate normal, univariate normal, regression, and discrete models Extensive examples throughout the text emphasize key concepts and different methodologies are used, namely the likelihood ratio criterion, and the Bayesian and information criterion approaches A comprehensive bibliography and two indices complete the study
Directory of Open Access Journals (Sweden)
Teresa Carmen Herrador Alcaide
2013-07-01
Full Text Available This article aims to establish a mathematical model to measure the performance of e-learning in adult distance education in the field of financial economics and accounting. As an innovative methodology, a ‘linear regression’ approach was applied to contrast correlations between variables in the model. A teacher innovation network was implemented for e-learning using different types of material. The compilation of data was carried out by means of an opinion survey to evaluate the usage of the four elements that comprised the design factors of the e-learning model applied at UNED. The contrast of a ‘Null Hypothesis’, e.g. by means of linear regression analysis, validated the established model. However, the ‘binary logistical analysis’ and the statistical contrast of the group demonstrated that the effect of e-learning on performance was not as high as it had been expected.
Cho, Hyun-Deok; Kim, Unyong; Suh, Joon Hyuk; Eom, Han Young; Kim, Junghyun; Lee, Seul Gi; Choi, Yong Seok; Han, Sang Beom
2016-04-01
Analytical methods using high-performance liquid chromatography with diode array and tandem mass spectrometry detection were developed for the discrimination of the rhizomes of four Atractylodes medicinal plants: A. japonica, A. macrocephala, A. chinensis, and A. lancea. A quantitative study was performed, selecting five bioactive components, including atractylenolide I, II, III, eudesma-4(14),7(11)-dien-8-one and atractylodin, on twenty-six Atractylodes samples of various origins. Sample extraction was optimized to sonication with 80% methanol for 40 min at room temperature. High-performance liquid chromatography with diode array detection was established using a C18 column with a water/acetonitrile gradient system at a flow rate of 1.0 mL/min, and the detection wavelength was set at 236 nm. Liquid chromatography with tandem mass spectrometry was applied to certify the reliability of the quantitative results. The developed methods were validated by ensuring specificity, linearity, limit of quantification, accuracy, precision, recovery, robustness, and stability. Results showed that cangzhu contained higher amounts of atractylenolide I and atractylodin than baizhu, and especially atractylodin contents showed the greatest variation between baizhu and cangzhu. Multivariate statistical analysis, such as principal component analysis and hierarchical cluster analysis, were also employed for further classification of the Atractylodes plants. The established method was suitable for quality control of the Atractylodes plants. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Statistical Analysis of Data for Timber Strengths
DEFF Research Database (Denmark)
Sørensen, John Dalsgaard
2003-01-01
Statistical analyses are performed for material strength parameters from a large number of specimens of structural timber. Non-parametric statistical analysis and fits have been investigated for the following distribution types: Normal, Lognormal, 2 parameter Weibull and 3-parameter Weibull...... fits to the data available, especially if tail fits are used whereas the Log Normal distribution generally gives a poor fit and larger coefficients of variation, especially if tail fits are used. The implications on the reliability level of typical structural elements and on partial safety factors...... for timber are investigated....
Analysis of Statistical Performance Measures
National Research Council Canada - National Science Library
Zoltowski, Michael D
2004-01-01
When only a limited number of snapshots is available for estimating the spatial correlation matrix, a low-rank solution of the MVDR equations, obtained via a small number of iterations of Conjugate Gradients (CG...
Statistical analysis of brake squeal noise
Oberst, S.; Lai, J. C. S.
2011-06-01
Despite substantial research efforts applied to the prediction of brake squeal noise since the early 20th century, the mechanisms behind its generation are still not fully understood. Squealing brakes are of significant concern to the automobile industry, mainly because of the costs associated with warranty claims. In order to remedy the problems inherent in designing quieter brakes and, therefore, to understand the mechanisms, a design of experiments study, using a noise dynamometer, was performed by a brake system manufacturer to determine the influence of geometrical parameters (namely, the number and location of slots) of brake pads on brake squeal noise. The experimental results were evaluated with a noise index and ranked for warm and cold brake stops. These data are analysed here using statistical descriptors based on population distributions, and a correlation analysis, to gain greater insight into the functional dependency between the time-averaged friction coefficient as the input and the peak sound pressure level data as the output quantity. The correlation analysis between the time-averaged friction coefficient and peak sound pressure data is performed by applying a semblance analysis and a joint recurrence quantification analysis. Linear measures are compared with complexity measures (nonlinear) based on statistics from the underlying joint recurrence plots. Results show that linear measures cannot be used to rank the noise performance of the four test pad configurations. On the other hand, the ranking of the noise performance of the test pad configurations based on the noise index agrees with that based on nonlinear measures: the higher the nonlinearity between the time-averaged friction coefficient and peak sound pressure, the worse the squeal. These results highlight the nonlinear character of brake squeal and indicate the potential of using nonlinear statistical analysis tools to analyse disc brake squeal.
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
Statistical analysis of management data
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.
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...
A Statistical Analysis of Cryptocurrencies
Directory of Open Access Journals (Sweden)
Stephen Chan
2017-05-01
Full Text Available We analyze statistical properties of the largest cryptocurrencies (determined by market capitalization, of which Bitcoin is the most prominent example. We characterize their exchange rates versus the U.S. Dollar by fitting parametric distributions to them. It is shown that returns are clearly non-normal, however, no single distribution fits well jointly to all the cryptocurrencies analysed. We find that for the most popular currencies, such as Bitcoin and Litecoin, the generalized hyperbolic distribution gives the best fit, while for the smaller cryptocurrencies the normal inverse Gaussian distribution, generalized t distribution, and Laplace distribution give good fits. The results are important for investment and risk management purposes.
Czech Academy of Sciences Publication Activity Database
Zavyalova, U.; Holeňa, Martin; Schlögl, R.; Baerns, M.
2011-01-01
Roč. 3, č. 12 (2011), s. 1935-1947 ISSN 1867-3880 Institutional research plan: CEZ:AV0Z10300504 Keywords : catalyst development * heterogeneous catalysis * methane * oxidative coupling * catalyst composition * statistical analysis Subject RIV: IN - Informatics, Computer Science Impact factor: 5.207, year: 2011
Directory of Open Access Journals (Sweden)
Obed M. Ali
2015-12-01
Full Text Available In this study, the fuel properties and engine performance of blended palm biodiesel-diesel using diethyl ether as additive have been investigated. The properties of B30 blended palm biodiesel-diesel fuel were measured and analyzed statistically with the addition of 2%, 4%, 6% and 8% (by volume diethyl ether additive. The engine tests were conducted at increasing engine speeds from 1500 rpm to 3500 rpm and under constant load. Optimization of independent variables was performed using the desirability approach of the response surface methodology (RSM with the goal of minimizing emissions and maximizing performance parameters. The experiments were designed using a statistical tool known as design of experiments (DoE based on RSM.
Statistical Analysis of Zebrafish Locomotor Response.
Liu, Yiwen; Carmer, Robert; Zhang, Gaonan; Venkatraman, Prahatha; Brown, Skye Ashton; Pang, Chi-Pui; Zhang, Mingzhi; Ma, Ping; Leung, Yuk Fai
2015-01-01
Zebrafish larvae display rich locomotor behaviour upon external stimulation. The movement can be simultaneously tracked from many larvae arranged in multi-well plates. The resulting time-series locomotor data have been used to reveal new insights into neurobiology and pharmacology. However, the data are of large scale, and the corresponding locomotor behavior is affected by multiple factors. These issues pose a statistical challenge for comparing larval activities. To address this gap, this study has analyzed a visually-driven locomotor behaviour named the visual motor response (VMR) by the Hotelling's T-squared test. This test is congruent with comparing locomotor profiles from a time period. Different wild-type (WT) strains were compared using the test, which shows that they responded differently to light change at different developmental stages. The performance of this test was evaluated by a power analysis, which shows that the test was sensitive for detecting differences between experimental groups with sample numbers that were commonly used in various studies. In addition, this study investigated the effects of various factors that might affect the VMR by multivariate analysis of variance (MANOVA). The results indicate that the larval activity was generally affected by stage, light stimulus, their interaction, and location in the plate. Nonetheless, different factors affected larval activity differently over time, as indicated by a dynamical analysis of the activity at each second. Intriguingly, this analysis also shows that biological and technical repeats had negligible effect on larval activity. This finding is consistent with that from the Hotelling's T-squared test, and suggests that experimental repeats can be combined to enhance statistical power. Together, these investigations have established a statistical framework for analyzing VMR data, a framework that should be generally applicable to other locomotor data with similar structure.
Statistical methods for astronomical data analysis
Chattopadhyay, Asis Kumar
2014-01-01
This book introduces “Astrostatistics” as a subject in its own right with rewarding examples, including work by the authors with galaxy and Gamma Ray Burst data to engage the reader. This includes a comprehensive blending of Astrophysics and Statistics. The first chapter’s coverage of preliminary concepts and terminologies for astronomical phenomenon will appeal to both Statistics and Astrophysics readers as helpful context. Statistics concepts covered in the book provide a methodological framework. A unique feature is the inclusion of different possible sources of astronomical data, as well as software packages for converting the raw data into appropriate forms for data analysis. Readers can then use the appropriate statistical packages for their particular data analysis needs. The ideas of statistical inference discussed in the book help readers determine how to apply statistical tests. The authors cover different applications of statistical techniques already developed or specifically introduced for ...
Statistical analysis with Excel for dummies
Schmuller, Joseph
2013-01-01
Take the mystery out of statistical terms and put Excel to work! If you need to create and interpret statistics in business or classroom settings, this easy-to-use guide is just what you need. It shows you how to use Excel's powerful tools for statistical analysis, even if you've never taken a course in statistics. Learn the meaning of terms like mean and median, margin of error, standard deviation, and permutations, and discover how to interpret the statistics of everyday life. You'll learn to use Excel formulas, charts, PivotTables, and other tools to make sense of everything fro
Collecting operational event data for statistical analysis
International Nuclear Information System (INIS)
Atwood, C.L.
1994-09-01
This report gives guidance for collecting operational data to be used for statistical analysis, especially analysis of event counts. It discusses how to define the purpose of the study, the unit (system, component, etc.) to be studied, events to be counted, and demand or exposure time. Examples are given of classification systems for events in the data sources. A checklist summarizes the essential steps in data collection for statistical analysis
Explorations in Statistics: The Analysis of Change
Curran-Everett, Douglas; Williams, Calvin L.
2015-01-01
Learning about statistics is a lot like learning about science: the learning is more meaningful if you can actively explore. This tenth installment of "Explorations in Statistics" explores the analysis of a potential change in some physiological response. As researchers, we often express absolute change as percent change so we can…
Statistics Anxiety, Trait Anxiety, Learning Behavior, and Academic Performance
Macher, Daniel; Paechter, Manuela; Papousek, Ilona; Ruggeri, Kai
2012-01-01
The present study investigated the relationship between statistics anxiety, individual characteristics (e.g., trait anxiety and learning strategies), and academic performance. Students enrolled in a statistics course in psychology (N = 147) filled in a questionnaire on statistics anxiety, trait anxiety, interest in statistics, mathematical…
Statistical shape analysis with applications in R
Dryden, Ian L
2016-01-01
A thoroughly revised and updated edition of this introduction to modern statistical methods for shape analysis Shape analysis is an important tool in the many disciplines where objects are compared using geometrical features. Examples include comparing brain shape in schizophrenia; investigating protein molecules in bioinformatics; and describing growth of organisms in biology. This book is a significant update of the highly-regarded `Statistical Shape Analysis’ by the same authors. The new edition lays the foundations of landmark shape analysis, including geometrical concepts and statistical techniques, and extends to include analysis of curves, surfaces, images and other types of object data. Key definitions and concepts are discussed throughout, and the relative merits of different approaches are presented. The authors have included substantial new material on recent statistical developments and offer numerous examples throughout the text. Concepts are introduced in an accessible manner, while reta...
Spatial analysis statistics, visualization, and computational methods
Oyana, Tonny J
2015-01-01
An introductory text for the next generation of geospatial analysts and data scientists, Spatial Analysis: Statistics, Visualization, and Computational Methods focuses on the fundamentals of spatial analysis using traditional, contemporary, and computational methods. Outlining both non-spatial and spatial statistical concepts, the authors present practical applications of geospatial data tools, techniques, and strategies in geographic studies. They offer a problem-based learning (PBL) approach to spatial analysis-containing hands-on problem-sets that can be worked out in MS Excel or ArcGIS-as well as detailed illustrations and numerous case studies. The book enables readers to: Identify types and characterize non-spatial and spatial data Demonstrate their competence to explore, visualize, summarize, analyze, optimize, and clearly present statistical data and results Construct testable hypotheses that require inferential statistical analysis Process spatial data, extract explanatory variables, conduct statisti...
Advances in statistical models for data analysis
Minerva, Tommaso; Vichi, Maurizio
2015-01-01
This edited volume focuses on recent research results in classification, multivariate statistics and machine learning and highlights advances in statistical models for data analysis. The volume provides both methodological developments and contributions to a wide range of application areas such as economics, marketing, education, social sciences and environment. The papers in this volume were first presented at the 9th biannual meeting of the Classification and Data Analysis Group (CLADAG) of the Italian Statistical Society, held in September 2013 at the University of Modena and Reggio Emilia, Italy.
Bonald, Thomas
2013-01-01
The book presents some key mathematical tools for the performance analysis of communication networks and computer systems.Communication networks and computer systems have become extremely complex. The statistical resource sharing induced by the random behavior of users and the underlying protocols and algorithms may affect Quality of Service.This book introduces the main results of queuing theory that are useful for analyzing the performance of these systems. These mathematical tools are key to the development of robust dimensioning rules and engineering methods. A number of examples i
Classification, (big) data analysis and statistical learning
Conversano, Claudio; Vichi, Maurizio
2018-01-01
This edited book focuses on the latest developments in classification, statistical learning, data analysis and related areas of data science, including statistical analysis of large datasets, big data analytics, time series clustering, integration of data from different sources, as well as social networks. It covers both methodological aspects as well as applications to a wide range of areas such as economics, marketing, education, social sciences, medicine, environmental sciences and the pharmaceutical industry. In addition, it describes the basic features of the software behind the data analysis results, and provides links to the corresponding codes and data sets where necessary. This book is intended for researchers and practitioners who are interested in the latest developments and applications in the field. The peer-reviewed contributions were presented at the 10th Scientific Meeting of the Classification and Data Analysis Group (CLADAG) of the Italian Statistical Society, held in Santa Margherita di Pul...
Statistical hot spot analysis of reactor cores
International Nuclear Information System (INIS)
Schaefer, H.
1974-05-01
This report is an introduction into statistical hot spot analysis. After the definition of the term 'hot spot' a statistical analysis is outlined. The mathematical method is presented, especially the formula concerning the probability of no hot spots in a reactor core is evaluated. A discussion with the boundary conditions of a statistical hot spot analysis is given (technological limits, nominal situation, uncertainties). The application of the hot spot analysis to the linear power of pellets and the temperature rise in cooling channels is demonstrated with respect to the test zone of KNK II. Basic values, such as probability of no hot spots, hot spot potential, expected hot spot diagram and cumulative distribution function of hot spots, are discussed. It is shown, that the risk of hot channels can be dispersed equally over all subassemblies by an adequate choice of the nominal temperature distribution in the core
Statistical analysis of angular correlation measurements
International Nuclear Information System (INIS)
Oliveira, R.A.A.M. de.
1986-01-01
Obtaining the multipole mixing ratio, δ, of γ transitions in angular correlation measurements is a statistical problem characterized by the small number of angles in which the observation is made and by the limited statistic of counting, α. The inexistence of a sufficient statistics for the estimator of δ, is shown. Three different estimators for δ were constructed and their properties of consistency, bias and efficiency were tested. Tests were also performed in experimental results obtained in γ-γ directional correlation measurements. (Author) [pt
Statistics and analysis of scientific data
Bonamente, Massimiliano
2013-01-01
Statistics and Analysis of Scientific Data covers the foundations of probability theory and statistics, and a number of numerical and analytical methods that are essential for the present-day analyst of scientific data. Topics covered include probability theory, distribution functions of statistics, fits to two-dimensional datasheets and parameter estimation, Monte Carlo methods and Markov chains. Equal attention is paid to the theory and its practical application, and results from classic experiments in various fields are used to illustrate the importance of statistics in the analysis of scientific data. The main pedagogical method is a theory-then-application approach, where emphasis is placed first on a sound understanding of the underlying theory of a topic, which becomes the basis for an efficient and proactive use of the material for practical applications. The level is appropriate for undergraduates and beginning graduate students, and as a reference for the experienced researcher. Basic calculus is us...
Rweb:Web-based Statistical Analysis
Directory of Open Access Journals (Sweden)
Jeff Banfield
1999-03-01
Full Text Available Rweb is a freely accessible statistical analysis environment that is delivered through the World Wide Web (WWW. It is based on R, a well known statistical analysis package. The only requirement to run the basic Rweb interface is a WWW browser that supports forms. If you want graphical output you must, of course, have a browser that supports graphics. The interface provides access to WWW accessible data sets, so you may run Rweb on your own data. Rweb can provide a four window statistical computing environment (code input, text output, graphical output, and error information through browsers that support Javascript. There is also a set of point and click modules under development for use in introductory statistics courses.
Semiclassical analysis, Witten Laplacians, and statistical mechanis
Helffer, Bernard
2002-01-01
This important book explains how the technique of Witten Laplacians may be useful in statistical mechanics. It considers the problem of analyzing the decay of correlations, after presenting its origin in statistical mechanics. In addition, it compares the Witten Laplacian approach with other techniques, such as the transfer matrix approach and its semiclassical analysis. The author concludes by providing a complete proof of the uniform Log-Sobolev inequality. Contents: Witten Laplacians Approach; Problems in Statistical Mechanics with Discrete Spins; Laplace Integrals and Transfer Operators; S
A statistical approach to plasma profile analysis
International Nuclear Information System (INIS)
Kardaun, O.J.W.F.; McCarthy, P.J.; Lackner, K.; Riedel, K.S.
1990-05-01
A general statistical approach to the parameterisation and analysis of tokamak profiles is presented. The modelling of the profile dependence on both the radius and the plasma parameters is discussed, and pertinent, classical as well as robust, methods of estimation are reviewed. Special attention is given to statistical tests for discriminating between the various models, and to the construction of confidence intervals for the parameterised profiles and the associated global quantities. The statistical approach is shown to provide a rigorous approach to the empirical testing of plasma profile invariance. (orig.)
Reproducible statistical analysis with multiple languages
DEFF Research Database (Denmark)
Lenth, Russell; Højsgaard, Søren
2011-01-01
This paper describes the system for making reproducible statistical analyses. differs from other systems for reproducible analysis in several ways. The two main differences are: (1) Several statistics programs can be in used in the same document. (2) Documents can be prepared using OpenOffice or ......Office or \\LaTeX. The main part of this paper is an example showing how to use and together in an OpenOffice text document. The paper also contains some practical considerations on the use of literate programming in statistics....
Foundation of statistical energy analysis in vibroacoustics
Le Bot, A
2015-01-01
This title deals with the statistical theory of sound and vibration. The foundation of statistical energy analysis is presented in great detail. In the modal approach, an introduction to random vibration with application to complex systems having a large number of modes is provided. For the wave approach, the phenomena of propagation, group speed, and energy transport are extensively discussed. Particular emphasis is given to the emergence of diffuse field, the central concept of the theory.
A Statistical Toolkit for Data Analysis
International Nuclear Information System (INIS)
Donadio, S.; Guatelli, S.; Mascialino, B.; Pfeiffer, A.; Pia, M.G.; Ribon, A.; Viarengo, P.
2006-01-01
The present project aims to develop an open-source and object-oriented software Toolkit for statistical data analysis. Its statistical testing component contains a variety of Goodness-of-Fit tests, from Chi-squared to Kolmogorov-Smirnov, to less known, but generally much more powerful tests such as Anderson-Darling, Goodman, Fisz-Cramer-von Mises, Kuiper, Tiku. Thanks to the component-based design and the usage of the standard abstract interfaces for data analysis, this tool can be used by other data analysis systems or integrated in experimental software frameworks. This Toolkit has been released and is downloadable from the web. In this paper we describe the statistical details of the algorithms, the computational features of the Toolkit and describe the code validation
Analysis of statistical misconception in terms of statistical reasoning
Maryati, I.; Priatna, N.
2018-05-01
Reasoning skill is needed for everyone to face globalization era, because every person have to be able to manage and use information from all over the world which can be obtained easily. Statistical reasoning skill is the ability to collect, group, process, interpret, and draw conclusion of information. Developing this skill can be done through various levels of education. However, the skill is low because many people assume that statistics is just the ability to count and using formulas and so do students. Students still have negative attitude toward course which is related to research. The purpose of this research is analyzing students’ misconception in descriptive statistic course toward the statistical reasoning skill. The observation was done by analyzing the misconception test result and statistical reasoning skill test; observing the students’ misconception effect toward statistical reasoning skill. The sample of this research was 32 students of math education department who had taken descriptive statistic course. The mean value of misconception test was 49,7 and standard deviation was 10,6 whereas the mean value of statistical reasoning skill test was 51,8 and standard deviation was 8,5. If the minimal value is 65 to state the standard achievement of a course competence, students’ mean value is lower than the standard competence. The result of students’ misconception study emphasized on which sub discussion that should be considered. Based on the assessment result, it was found that students’ misconception happen on this: 1) writing mathematical sentence and symbol well, 2) understanding basic definitions, 3) determining concept that will be used in solving problem. In statistical reasoning skill, the assessment was done to measure reasoning from: 1) data, 2) representation, 3) statistic format, 4) probability, 5) sample, and 6) association.
STATISTICS, Program System for Statistical Analysis of Experimental Data
International Nuclear Information System (INIS)
Helmreich, F.
1991-01-01
1 - Description of problem or function: The package is composed of 83 routines, the most important of which are the following: BINDTR: Binomial distribution; HYPDTR: Hypergeometric distribution; POIDTR: Poisson distribution; GAMDTR: Gamma distribution; BETADTR: Beta-1 and Beta-2 distributions; NORDTR: Normal distribution; CHIDTR: Chi-square distribution; STUDTR : Distribution of 'Student's T'; FISDTR: Distribution of F; EXPDTR: Exponential distribution; WEIDTR: Weibull distribution; FRAKTIL: Calculation of the fractiles of the normal, chi-square, Student's, and F distributions; VARVGL: Test for equality of variance for several sample observations; ANPAST: Kolmogorov-Smirnov test and chi-square test of goodness of fit; MULIRE: Multiple linear regression analysis for a dependent variable and a set of independent variables; STPRG: Performs a stepwise multiple linear regression analysis for a dependent variable and a set of independent variables. At each step, the variable entered into the regression equation is the one which has the greatest amount of variance between it and the dependent variable. Any independent variable can be forced into or deleted from the regression equation, irrespective of its contribution to the equation. LTEST: Tests the hypotheses of linearity of the data. SPRANK: Calculates the Spearman rank correlation coefficient. 2 - Method of solution: VARVGL: The Bartlett's Test, the Cochran's Test and the Hartley's Test are performed in the program. MULIRE: The Gauss-Jordan method is used in the solution of the normal equations. STPRG: The abbreviated Doolittle method is used to (1) determine variables to enter into the regression, and (2) complete regression coefficient calculation. 3 - Restrictions on the complexity of the problem: VARVGL: The Hartley's Test is only performed if the sample observations are all of the same size
Statistical analysis of network data with R
Kolaczyk, Eric D
2014-01-01
Networks have permeated everyday life through everyday realities like the Internet, social networks, and viral marketing. As such, network analysis is an important growth area in the quantitative sciences, with roots in social network analysis going back to the 1930s and graph theory going back centuries. Measurement and analysis are integral components of network research. As a result, statistical methods play a critical role in network analysis. This book is the first of its kind in network research. It can be used as a stand-alone resource in which multiple R packages are used to illustrate how to conduct a wide range of network analyses, from basic manipulation and visualization, to summary and characterization, to modeling of network data. The central package is igraph, which provides extensive capabilities for studying network graphs in R. This text builds on Eric D. Kolaczyk’s book Statistical Analysis of Network Data (Springer, 2009).
A Model of Statistics Performance Based on Achievement Goal Theory.
Bandalos, Deborah L.; Finney, Sara J.; Geske, Jenenne A.
2003-01-01
Tests a model of statistics performance based on achievement goal theory. Both learning and performance goals affected achievement indirectly through study strategies, self-efficacy, and test anxiety. Implications of these findings for teaching and learning statistics are discussed. (Contains 47 references, 3 tables, 3 figures, and 1 appendix.)…
Statistics and analysis of scientific data
Bonamente, Massimiliano
2017-01-01
The revised second edition of this textbook provides the reader with a solid foundation in probability theory and statistics as applied to the physical sciences, engineering and related fields. It covers a broad range of numerical and analytical methods that are essential for the correct analysis of scientific data, including probability theory, distribution functions of statistics, fits to two-dimensional data and parameter estimation, Monte Carlo methods and Markov chains. Features new to this edition include: • a discussion of statistical techniques employed in business science, such as multiple regression analysis of multivariate datasets. • a new chapter on the various measures of the mean including logarithmic averages. • new chapters on systematic errors and intrinsic scatter, and on the fitting of data with bivariate errors. • a new case study and additional worked examples. • mathematical derivations and theoretical background material have been appropriately marked,to improve the readabili...
Statistical analysis on extreme wave height
Digital Repository Service at National Institute of Oceanography (India)
Teena, N.V.; SanilKumar, V.; Sudheesh, K.; Sajeev, R.
-294. • WAFO (2000) – A MATLAB toolbox for analysis of random waves and loads, Lund University, Sweden, homepage http://www.maths.lth.se/matstat/wafo/,2000. 15 Table 1: Statistical results of data and fitted distribution for cumulative distribution...
Applied Behavior Analysis and Statistical Process Control?
Hopkins, B. L.
1995-01-01
Incorporating statistical process control (SPC) methods into applied behavior analysis is discussed. It is claimed that SPC methods would likely reduce applied behavior analysts' intimate contacts with problems and would likely yield poor treatment and research decisions. Cases and data presented by Pfadt and Wheeler (1995) are cited as examples.…
The fuzzy approach to statistical analysis
Coppi, Renato; Gil, Maria A.; Kiers, Henk A. L.
2006-01-01
For the last decades, research studies have been developed in which a coalition of Fuzzy Sets Theory and Statistics has been established with different purposes. These namely are: (i) to introduce new data analysis problems in which the objective involves either fuzzy relationships or fuzzy terms;
Plasma data analysis using statistical analysis system
International Nuclear Information System (INIS)
Yoshida, Z.; Iwata, Y.; Fukuda, Y.; Inoue, N.
1987-01-01
Multivariate factor analysis has been applied to a plasma data base of REPUTE-1. The characteristics of the reverse field pinch plasma in REPUTE-1 are shown to be explained by four independent parameters which are described in the report. The well known scaling laws F/sub chi/ proportional to I/sub p/, T/sub e/ proportional to I/sub p/, and tau/sub E/ proportional to N/sub e/ are also confirmed. 4 refs., 8 figs., 1 tab
Statistical analysis of metallicity in spiral galaxies
Energy Technology Data Exchange (ETDEWEB)
Galeotti, P [Consiglio Nazionale delle Ricerche, Turin (Italy). Lab. di Cosmo-Geofisica; Turin Univ. (Italy). Ist. di Fisica Generale)
1981-04-01
A principal component analysis of metallicity and other integral properties of 33 spiral galaxies is presented; the involved parameters are: morphological type, diameter, luminosity and metallicity. From the statistical analysis it is concluded that the sample has only two significant dimensions and additonal tests, involving different parameters, show similar results. Thus it seems that only type and luminosity are independent variables, being the other integral properties of spiral galaxies correlated with them.
Selected papers on analysis, probability, and statistics
Nomizu, Katsumi
1994-01-01
This book presents papers that originally appeared in the Japanese journal Sugaku. The papers fall into the general area of mathematical analysis as it pertains to probability and statistics, dynamical systems, differential equations and analytic function theory. Among the topics discussed are: stochastic differential equations, spectra of the Laplacian and Schrödinger operators, nonlinear partial differential equations which generate dissipative dynamical systems, fractal analysis on self-similar sets and the global structure of analytic functions.
Surface Properties of TNOs: Preliminary Statistical Analysis
Antonieta Barucci, Maria; Fornasier, S.; Alvarez-Cantal, A.; de Bergh, C.; Merlin, F.; DeMeo, F.; Dumas, C.
2009-09-01
An overview of the surface properties based on the last results obtained during the Large Program performed at ESO-VLT (2007-2008) will be presented. Simultaneous high quality visible and near-infrared spectroscopy and photometry have been carried out on 40 objects with various dynamical properties, using FORS1 (V), ISAAC (J) and SINFONI (H+K bands) mounted respectively at UT2, UT1 and UT4 VLT-ESO telescopes (Cerro Paranal, Chile). For spectroscopy we computed the spectral slope for each object and searched for possible rotational inhomogeneities. A few objects show features in their visible spectra such as Eris, whose spectral bands are displaced with respect to pure methane-ice. We identify new faint absorption features on 10199 Chariklo and 42355 Typhon, possibly due to the presence of aqueous altered materials. The H+K band spectroscopy was performed with the new instrument SINFONI which is a 3D integral field spectrometer. While some objects show no diagnostic spectral bands, others reveal surface deposits of ices of H2O, CH3OH, CH4, and N2. To investigate the surface properties of these bodies, a radiative transfer model has been applied to interpret the entire 0.4-2.4 micron spectral region. The diversity of the spectra suggests that these objects represent a substantial range of bulk compositions. These different surface compositions can be diagnostic of original compositional diversity, interior source and/or different evolution with different physical processes affecting the surfaces. A statistical analysis is in progress to investigate the correlation of the TNOs’ surface properties with size and dynamical properties.
The Statistical Analysis of Time Series
Anderson, T W
2011-01-01
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 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 George
A statistical approach to nuclear fuel design and performance
Cunning, Travis Andrew
As CANDU fuel failures can have significant economic and operational consequences on the Canadian nuclear power industry, it is essential that factors impacting fuel performance are adequately understood. Current industrial practice relies on deterministic safety analysis and the highly conservative "limit of operating envelope" approach, where all parameters are assumed to be at their limits simultaneously. This results in a conservative prediction of event consequences with little consideration given to the high quality and precision of current manufacturing processes. This study employs a novel approach to the prediction of CANDU fuel reliability. Probability distributions are fitted to actual fuel manufacturing datasets provided by Cameco Fuel Manufacturing, Inc. They are used to form input for two industry-standard fuel performance codes: ELESTRES for the steady-state case and ELOCA for the transient case---a hypothesized 80% reactor outlet header break loss of coolant accident. Using a Monte Carlo technique for input generation, 105 independent trials are conducted and probability distributions are fitted to key model output quantities. Comparing model output against recognized industrial acceptance criteria, no fuel failures are predicted for either case. Output distributions are well removed from failure limit values, implying that margin exists in current fuel manufacturing and design. To validate the results and attempt to reduce the simulation burden of the methodology, two dimensional reduction methods are assessed. Using just 36 trials, both methods are able to produce output distributions that agree strongly with those obtained via the brute-force Monte Carlo method, often to a relative discrepancy of less than 0.3% when predicting the first statistical moment, and a relative discrepancy of less than 5% when predicting the second statistical moment. In terms of global sensitivity, pellet density proves to have the greatest impact on fuel performance
Developments in statistical analysis in quantitative genetics
DEFF Research Database (Denmark)
Sorensen, Daniel
2009-01-01
of genetic means and variances, models for the analysis of categorical and count data, the statistical genetics of a model postulating that environmental variance is partly under genetic control, and a short discussion of models that incorporate massive genetic marker information. We provide an overview......A remarkable research impetus has taken place in statistical genetics since the last World Conference. This has been stimulated by breakthroughs in molecular genetics, automated data-recording devices and computer-intensive statistical methods. The latter were revolutionized by the bootstrap...... and by Markov chain Monte Carlo (McMC). In this overview a number of specific areas are chosen to illustrate the enormous flexibility that McMC has provided for fitting models and exploring features of data that were previously inaccessible. The selected areas are inferences of the trajectories over time...
Statistical Analysis of Big Data on Pharmacogenomics
Fan, Jianqing; Liu, Han
2013-01-01
This paper discusses statistical methods for estimating complex correlation structure from large pharmacogenomic datasets. We selectively review several prominent statistical methods for estimating large covariance matrix for understanding correlation structure, inverse covariance matrix for network modeling, large-scale simultaneous tests for selecting significantly differently expressed genes and proteins and genetic markers for complex diseases, and high dimensional variable selection for identifying important molecules for understanding molecule mechanisms in pharmacogenomics. Their applications to gene network estimation and biomarker selection are used to illustrate the methodological power. Several new challenges of Big data analysis, including complex data distribution, missing data, measurement error, spurious correlation, endogeneity, and the need for robust statistical methods, are also discussed. PMID:23602905
Statistical analysis of next generation sequencing data
Nettleton, Dan
2014-01-01
Next Generation Sequencing (NGS) is the latest high throughput technology to revolutionize genomic research. NGS generates massive genomic datasets that play a key role in the big data phenomenon that surrounds us today. To extract signals from high-dimensional NGS data and make valid statistical inferences and predictions, novel data analytic and statistical techniques are needed. This book contains 20 chapters written by prominent statisticians working with NGS data. The topics range from basic preprocessing and analysis with NGS data to more complex genomic applications such as copy number variation and isoform expression detection. Research statisticians who want to learn about this growing and exciting area will find this book useful. In addition, many chapters from this book could be included in graduate-level classes in statistical bioinformatics for training future biostatisticians who will be expected to deal with genomic data in basic biomedical research, genomic clinical trials and personalized med...
Robust statistics and geochemical data analysis
International Nuclear Information System (INIS)
Di, Z.
1987-01-01
Advantages of robust procedures over ordinary least-squares procedures in geochemical data analysis is demonstrated using NURE data from the Hot Springs Quadrangle, South Dakota, USA. Robust principal components analysis with 5% multivariate trimming successfully guarded the analysis against perturbations by outliers and increased the number of interpretable factors. Regression with SINE estimates significantly increased the goodness-of-fit of the regression and improved the correspondence of delineated anomalies with known uranium prospects. Because of the ubiquitous existence of outliers in geochemical data, robust statistical procedures are suggested as routine procedures to replace ordinary least-squares procedures
Analysis of photon statistics with Silicon Photomultiplier
International Nuclear Information System (INIS)
D'Ascenzo, N.; Saveliev, V.; Wang, L.; Xie, Q.
2015-01-01
The Silicon Photomultiplier (SiPM) is a novel silicon-based photodetector, which represents the modern perspective of low photon flux detection. The aim of this paper is to provide an introduction on the statistical analysis methods needed to understand and estimate in quantitative way the correct features and description of the response of the SiPM to a coherent source of light
Vapor Pressure Data Analysis and Statistics
2016-12-01
near 8, 2000, and 200, respectively. The A (or a) value is directly related to vapor pressure and will be greater for high vapor pressure materials...1, (10) where n is the number of data points, Yi is the natural logarithm of the i th experimental vapor pressure value, and Xi is the...VAPOR PRESSURE DATA ANALYSIS AND STATISTICS ECBC-TR-1422 Ann Brozena RESEARCH AND TECHNOLOGY DIRECTORATE
Statistical analysis of dragline monitoring data
Energy Technology Data Exchange (ETDEWEB)
Mirabediny, H.; Baafi, E.Y. [University of Tehran, Tehran (Iran)
1998-07-01
Dragline monitoring systems are normally the best tool used to collect data on the machine performance and operational parameters of a dragline operation. This paper discusses results of a time study using data from a dragline monitoring system captured over a four month period. Statistical summaries of the time study in terms of average values, standard deviation and frequency distributions showed that the mode of operation and the geological conditions have a significant influence on the dragline performance parameters. 6 refs., 14 figs., 3 tabs.
Uncertainty analysis with statistically correlated failure data
International Nuclear Information System (INIS)
Modarres, M.; Dezfuli, H.; Roush, M.L.
1987-01-01
Likelihood of occurrence of the top event of a fault tree or sequences of an event tree is estimated from the failure probability of components that constitute the events of the fault/event tree. Component failure probabilities are subject to statistical uncertainties. In addition, there are cases where the failure data are statistically correlated. At present most fault tree calculations are based on uncorrelated component failure data. This chapter describes a methodology for assessing the probability intervals for the top event failure probability of fault trees or frequency of occurrence of event tree sequences when event failure data are statistically correlated. To estimate mean and variance of the top event, a second-order system moment method is presented through Taylor series expansion, which provides an alternative to the normally used Monte Carlo method. For cases where component failure probabilities are statistically correlated, the Taylor expansion terms are treated properly. Moment matching technique is used to obtain the probability distribution function of the top event through fitting the Johnson Ssub(B) distribution. The computer program, CORRELATE, was developed to perform the calculations necessary for the implementation of the method developed. (author)
Sensitivity analysis and related analysis : A survey of statistical techniques
Kleijnen, J.P.C.
1995-01-01
This paper reviews the state of the art in five related types of analysis, namely (i) sensitivity or what-if analysis, (ii) uncertainty or risk analysis, (iii) screening, (iv) validation, and (v) optimization. The main question is: when should which type of analysis be applied; which statistical
Statistical analysis of dynamic parameters of the core
International Nuclear Information System (INIS)
Ionov, V.S.
2007-01-01
The transients of various types were investigated for the cores of zero power critical facilities in RRC KI and NPP. Dynamic parameters of neutron transients were explored by tool statistical analysis. Its have sufficient duration, few channels for currents of chambers and reactivity and also some channels for technological parameters. On these values the inverse period. reactivity, lifetime of neutrons, reactivity coefficients and some effects of a reactivity are determinate, and on the values were restored values of measured dynamic parameters as result of the analysis. The mathematical means of statistical analysis were used: approximation(A), filtration (F), rejection (R), estimation of parameters of descriptive statistic (DSP), correlation performances (kk), regression analysis(KP), the prognosis (P), statistician criteria (SC). The calculation procedures were realized by computer language MATLAB. The reasons of methodical and statistical errors are submitted: inadequacy of model operation, precision neutron-physical parameters, features of registered processes, used mathematical model in reactivity meters, technique of processing for registered data etc. Examples of results of statistical analysis. Problems of validity of the methods used for definition and certification of values of statistical parameters and dynamic characteristics are considered (Authors)
Analysis of Variance in Statistical Image Processing
Kurz, Ludwik; Hafed Benteftifa, M.
1997-04-01
A key problem in practical image processing is the detection of specific features in a noisy image. Analysis of variance (ANOVA) techniques can be very effective in such situations, and this book gives a detailed account of the use of ANOVA in statistical image processing. The book begins by describing the statistical representation of images in the various ANOVA models. The authors present a number of computationally efficient algorithms and techniques to deal with such problems as line, edge, and object detection, as well as image restoration and enhancement. By describing the basic principles of these techniques, and showing their use in specific situations, the book will facilitate the design of new algorithms for particular applications. It will be of great interest to graduate students and engineers in the field of image processing and pattern recognition.
HistFitter software framework for statistical data analysis
Baak, M.; Côte, D.; Koutsman, A.; Lorenz, J.; Short, D.
2015-01-01
We present a software framework for statistical data analysis, called HistFitter, that has been used extensively by the ATLAS Collaboration to analyze big datasets originating from proton-proton collisions at the Large Hadron Collider at CERN. Since 2012 HistFitter has been the standard statistical tool in searches for supersymmetric particles performed by ATLAS. HistFitter is a programmable and flexible framework to build, book-keep, fit, interpret and present results of data models of nearly arbitrary complexity. Starting from an object-oriented configuration, defined by users, the framework builds probability density functions that are automatically fitted to data and interpreted with statistical tests. A key innovation of HistFitter is its design, which is rooted in core analysis strategies of particle physics. The concepts of control, signal and validation regions are woven into its very fabric. These are progressively treated with statistically rigorous built-in methods. Being capable of working with mu...
On the Statistical Validation of Technical Analysis
Directory of Open Access Journals (Sweden)
Rosane Riera Freire
2007-06-01
Full Text Available Technical analysis, or charting, aims on visually identifying geometrical patterns in price charts in order to antecipate price "trends". In this paper we revisit the issue of thecnical analysis validation which has been tackled in the literature without taking care for (i the presence of heterogeneity and (ii statistical dependence in the analyzed data - various agglutinated return time series from distinct financial securities. The main purpose here is to address the first cited problem by suggesting a validation methodology that also "homogenizes" the securities according to the finite dimensional probability distribution of their return series. The general steps go through the identification of the stochastic processes for the securities returns, the clustering of similar securities and, finally, the identification of presence, or absence, of informatinal content obtained from those price patterns. We illustrate the proposed methodology with a real data exercise including several securities of the global market. Our investigation shows that there is a statistically significant informational content in two out of three common patterns usually found through technical analysis, namely: triangle, rectangle and head and shoulders.
Statistical trend analysis methods for temporal phenomena
International Nuclear Information System (INIS)
Lehtinen, E.; Pulkkinen, U.; Poern, K.
1997-04-01
We consider point events occurring in a random way in time. In many applications the pattern of occurrence is of intrinsic interest as indicating a trend or some other systematic feature in the rate of occurrence. The purpose of this report is to survey briefly different statistical trend analysis methods and illustrate their applicability to temporal phenomena in particular. The trend testing of point events is usually seen as the testing of the hypotheses concerning the intensity of the occurrence of events. When the intensity function is parametrized, the testing of trend is a typical parametric testing problem. In industrial applications the operational experience generally does not suggest any specified model and method in advance. Therefore, and particularly, if the Poisson process assumption is very questionable, it is desirable to apply tests that are valid for a wide variety of possible processes. The alternative approach for trend testing is to use some non-parametric procedure. In this report we have presented four non-parametric tests: The Cox-Stuart test, the Wilcoxon signed ranks test, the Mann test, and the exponential ordered scores test. In addition to the classical parametric and non-parametric approaches we have also considered the Bayesian trend analysis. First we discuss a Bayesian model, which is based on a power law intensity model. The Bayesian statistical inferences are based on the analysis of the posterior distribution of the trend parameters, and the probability of trend is immediately seen from these distributions. We applied some of the methods discussed in an example case. It should be noted, that this report is a feasibility study rather than a scientific evaluation of statistical methods, and the examples can only be seen as demonstrations of the methods
Statistical trend analysis methods for temporal phenomena
Energy Technology Data Exchange (ETDEWEB)
Lehtinen, E.; Pulkkinen, U. [VTT Automation, (Finland); Poern, K. [Poern Consulting, Nykoeping (Sweden)
1997-04-01
We consider point events occurring in a random way in time. In many applications the pattern of occurrence is of intrinsic interest as indicating a trend or some other systematic feature in the rate of occurrence. The purpose of this report is to survey briefly different statistical trend analysis methods and illustrate their applicability to temporal phenomena in particular. The trend testing of point events is usually seen as the testing of the hypotheses concerning the intensity of the occurrence of events. When the intensity function is parametrized, the testing of trend is a typical parametric testing problem. In industrial applications the operational experience generally does not suggest any specified model and method in advance. Therefore, and particularly, if the Poisson process assumption is very questionable, it is desirable to apply tests that are valid for a wide variety of possible processes. The alternative approach for trend testing is to use some non-parametric procedure. In this report we have presented four non-parametric tests: The Cox-Stuart test, the Wilcoxon signed ranks test, the Mann test, and the exponential ordered scores test. In addition to the classical parametric and non-parametric approaches we have also considered the Bayesian trend analysis. First we discuss a Bayesian model, which is based on a power law intensity model. The Bayesian statistical inferences are based on the analysis of the posterior distribution of the trend parameters, and the probability of trend is immediately seen from these distributions. We applied some of the methods discussed in an example case. It should be noted, that this report is a feasibility study rather than a scientific evaluation of statistical methods, and the examples can only be seen as demonstrations of the methods. 14 refs, 10 figs.
Self-assessed performance improves statistical fusion of image labels
International Nuclear Information System (INIS)
Bryan, Frederick W.; Xu, Zhoubing; Asman, Andrew J.; Allen, Wade M.; Reich, Daniel S.; Landman, Bennett A.
2014-01-01
Purpose: Expert manual labeling is the gold standard for image segmentation, but this process is difficult, time-consuming, and prone to inter-individual differences. While fully automated methods have successfully targeted many anatomies, automated methods have not yet been developed for numerous essential structures (e.g., the internal structure of the spinal cord as seen on magnetic resonance imaging). Collaborative labeling is a new paradigm that offers a robust alternative that may realize both the throughput of automation and the guidance of experts. Yet, distributing manual labeling expertise across individuals and sites introduces potential human factors concerns (e.g., training, software usability) and statistical considerations (e.g., fusion of information, assessment of confidence, bias) that must be further explored. During the labeling process, it is simple to ask raters to self-assess the confidence of their labels, but this is rarely done and has not been previously quantitatively studied. Herein, the authors explore the utility of self-assessment in relation to automated assessment of rater performance in the context of statistical fusion. Methods: The authors conducted a study of 66 volumes manually labeled by 75 minimally trained human raters recruited from the university undergraduate population. Raters were given 15 min of training during which they were shown examples of correct segmentation, and the online segmentation tool was demonstrated. The volumes were labeled 2D slice-wise, and the slices were unordered. A self-assessed quality metric was produced by raters for each slice by marking a confidence bar superimposed on the slice. Volumes produced by both voting and statistical fusion algorithms were compared against a set of expert segmentations of the same volumes. Results: Labels for 8825 distinct slices were obtained. Simple majority voting resulted in statistically poorer performance than voting weighted by self-assessed performance
Self-assessed performance improves statistical fusion of image labels
Energy Technology Data Exchange (ETDEWEB)
Bryan, Frederick W., E-mail: frederick.w.bryan@vanderbilt.edu; Xu, Zhoubing; Asman, Andrew J.; Allen, Wade M. [Electrical Engineering, Vanderbilt University, Nashville, Tennessee 37235 (United States); Reich, Daniel S. [Translational Neuroradiology Unit, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland 20892 (United States); Landman, Bennett A. [Electrical Engineering, Vanderbilt University, Nashville, Tennessee 37235 (United States); Biomedical Engineering, Vanderbilt University, Nashville, Tennessee 37235 (United States); and Radiology and Radiological Sciences, Vanderbilt University, Nashville, Tennessee 37235 (United States)
2014-03-15
Purpose: Expert manual labeling is the gold standard for image segmentation, but this process is difficult, time-consuming, and prone to inter-individual differences. While fully automated methods have successfully targeted many anatomies, automated methods have not yet been developed for numerous essential structures (e.g., the internal structure of the spinal cord as seen on magnetic resonance imaging). Collaborative labeling is a new paradigm that offers a robust alternative that may realize both the throughput of automation and the guidance of experts. Yet, distributing manual labeling expertise across individuals and sites introduces potential human factors concerns (e.g., training, software usability) and statistical considerations (e.g., fusion of information, assessment of confidence, bias) that must be further explored. During the labeling process, it is simple to ask raters to self-assess the confidence of their labels, but this is rarely done and has not been previously quantitatively studied. Herein, the authors explore the utility of self-assessment in relation to automated assessment of rater performance in the context of statistical fusion. Methods: The authors conducted a study of 66 volumes manually labeled by 75 minimally trained human raters recruited from the university undergraduate population. Raters were given 15 min of training during which they were shown examples of correct segmentation, and the online segmentation tool was demonstrated. The volumes were labeled 2D slice-wise, and the slices were unordered. A self-assessed quality metric was produced by raters for each slice by marking a confidence bar superimposed on the slice. Volumes produced by both voting and statistical fusion algorithms were compared against a set of expert segmentations of the same volumes. Results: Labels for 8825 distinct slices were obtained. Simple majority voting resulted in statistically poorer performance than voting weighted by self-assessed performance
Improved custom statistics visualization for CA Performance Center data
Talevi, Iacopo
2017-01-01
The main goal of my project is to understand and experiment the possibilities that CA Performance Center (CA PC) offers for creating custom applications to display stored information through interesting visual means, such as maps. In particular, I have re-written some of the network statistics web pages in order to fetch data from new statistics modules in CA PC, which has its own API, and stop using the RRD data.
Statistical analysis of solar proton events
Directory of Open Access Journals (Sweden)
V. Kurt
2004-06-01
Full Text Available A new catalogue of 253 solar proton events (SPEs with energy >10MeV and peak intensity >10 protons/cm2.s.sr (pfu at the Earth's orbit for three complete 11-year solar cycles (1970-2002 is given. A statistical analysis of this data set of SPEs and their associated flares that occurred during this time period is presented. It is outlined that 231 of these proton events are flare related and only 22 of them are not associated with Ha flares. It is also noteworthy that 42 of these events are registered as Ground Level Enhancements (GLEs in neutron monitors. The longitudinal distribution of the associated flares shows that a great number of these events are connected with west flares. This analysis enables one to understand the long-term dependence of the SPEs and the related flare characteristics on the solar cycle which are useful for space weather prediction.
Recent advances in statistical energy analysis
Heron, K. H.
1992-01-01
Statistical Energy Analysis (SEA) has traditionally been developed using modal summation and averaging approach, and has led to the need for many restrictive SEA assumptions. The assumption of 'weak coupling' is particularly unacceptable when attempts are made to apply SEA to structural coupling. It is now believed that this assumption is more a function of the modal formulation rather than a necessary formulation of SEA. The present analysis ignores this restriction and describes a wave approach to the calculation of plate-plate coupling loss factors. Predictions based on this method are compared with results obtained from experiments using point excitation on one side of an irregular six-sided box structure. Conclusions show that the use and calculation of infinite transmission coefficients is the way forward for the development of a purely predictive SEA code.
Implementation and statistical analysis of Metropolis algorithm for SU(3)
International Nuclear Information System (INIS)
Katznelson, E.; Nobile, A.
1984-12-01
In this paper we study the statistical properties of an implementation of the Metropolis algorithm for SU(3) gauge theory. It is shown that the results have normal distribution. We demonstrate that in this case error analysis can be carried on in a simple way and we show that applying it to both the measurement strategy and the output data analysis has an important influence on the performance and reliability of the simulation. (author)
Statistical analysis of tourism destination competitiveness
Directory of Open Access Journals (Sweden)
Attilio Gardini
2013-05-01
Full Text Available The growing relevance of tourism industry for modern advanced economies has increased the interest among researchers and policy makers in the statistical analysis of destination competitiveness. In this paper we outline a new model of destination competitiveness based on sound theoretical grounds and we develop a statistical test of the model on sample data based on Italian tourist destination decisions and choices. Our model focuses on the tourism decision process which starts from the demand schedule for holidays and ends with the choice of a specific holiday destination. The demand schedule is a function of individual preferences and of destination positioning, while the final decision is a function of the initial demand schedule and the information concerning services for accommodation and recreation in the selected destinations. Moreover, we extend previous studies that focused on image or attributes (such as climate and scenery by paying more attention to the services for accommodation and recreation in the holiday destinations. We test the proposed model using empirical data collected from a sample of 1.200 Italian tourists interviewed in 2007 (October - December. Data analysis shows that the selection probability for the destination included in the consideration set is not proportional to the share of inclusion because the share of inclusion is determined by the brand image, while the selection of the effective holiday destination is influenced by the real supply conditions. The analysis of Italian tourists preferences underline the existence of a latent demand for foreign holidays which points out a risk of market share reduction for Italian tourism system in the global market. We also find a snow ball effect which helps the most popular destinations, mainly in the northern Italian regions.
Attitude towards statistics and performance among post-graduate students
Rosli, Mira Khalisa; Maat, Siti Mistima
2017-05-01
For student to master Statistics is a necessity, especially for those post-graduates that are involved in the research field. The purpose of this research was to identify the attitude towards Statistics among the post-graduates and to determine the relationship between the attitude towards Statistics and post-graduates' of Faculty of Education, UKM, Bangi performance. 173 post-graduate students were chosen randomly to participate in the study. These students registered in Research Methodology II course that was introduced by faculty. A survey of attitude toward Statistics using 5-points Likert scale was used for data collection purposes. The instrument consists of four components such as affective, cognitive competency, value and difficulty. The data was analyzed using the SPSS version 22 in producing the descriptive and inferential Statistics output. The result of this research showed that there is a medium and positive relation between attitude towards statistics and students' performance. As a conclusion, educators need to access students' attitude towards the course to accomplish the learning outcomes.
Multivariate statistical analysis of wildfires in Portugal
Costa, Ricardo; Caramelo, Liliana; Pereira, Mário
2013-04-01
Several studies demonstrate that wildfires in Portugal present high temporal and spatial variability as well as cluster behavior (Pereira et al., 2005, 2011). This study aims to contribute to the characterization of the fire regime in Portugal with the multivariate statistical analysis of the time series of number of fires and area burned in Portugal during the 1980 - 2009 period. The data used in the analysis is an extended version of the Rural Fire Portuguese Database (PRFD) (Pereira et al, 2011), provided by the National Forest Authority (Autoridade Florestal Nacional, AFN), the Portuguese Forest Service, which includes information for more than 500,000 fire records. There are many multiple advanced techniques for examining the relationships among multiple time series at the same time (e.g., canonical correlation analysis, principal components analysis, factor analysis, path analysis, multiple analyses of variance, clustering systems). This study compares and discusses the results obtained with these different techniques. Pereira, M.G., Trigo, R.M., DaCamara, C.C., Pereira, J.M.C., Leite, S.M., 2005: "Synoptic patterns associated with large summer forest fires in Portugal". Agricultural and Forest Meteorology. 129, 11-25. Pereira, M. G., Malamud, B. D., Trigo, R. M., and Alves, P. I.: The history and characteristics of the 1980-2005 Portuguese rural fire database, Nat. Hazards Earth Syst. Sci., 11, 3343-3358, doi:10.5194/nhess-11-3343-2011, 2011 This work is supported by European Union Funds (FEDER/COMPETE - Operational Competitiveness Programme) and by national funds (FCT - Portuguese Foundation for Science and Technology) under the project FCOMP-01-0124-FEDER-022692, the project FLAIR (PTDC/AAC-AMB/104702/2008) and the EU 7th Framework Program through FUME (contract number 243888).
THESEE-3, Orgel Reactor Performance and Statistic Hot Channel Factors
International Nuclear Information System (INIS)
Chambaud, B.
1974-01-01
1 - Nature of physical problem solved: The code applies to a heavy-water moderated organic-cooled reactor channel. Different fuel cluster models can be used (circular or hexagonal patterns). The code gives coolant temperatures and velocities and cladding temperatures throughout the channel and also channel performances, such as power, outlet temperature, boiling and burn-out safety margins (see THESEE-1). In a further step, calculations are performed with statistical values obtained by random retrieval of geometrical in- put data and taking into account construction tolerances, vibrations, etc. The code evaluates the mean value and standard deviation for the more important thermal and hydraulic parameters. 2 - Method of solution: First step calculations are performed for nominal values of parameters by solving iteratively the non-linear system of equations which give the pressure drops in subchannels of the current zone (see THESEE-1). Then a Gaussian probability distribution of possible statistical values of the geometrical input data is assumed. A random number generation routine determines the statistical case. Calculations are performed in the same way as for the nominal case. In the case of several channels, statistical performances must be adjusted to equalize the normal pressure drop. A special subroutine (AVERAGE) then determines the mean value and standard deviation, and thus probability functions of the most significant thermal and hydraulic results. 3 - Restrictions on the complexity of the problem: Maximum 7 fuel clusters, each divided into 10 axial zones. Fuel bundle geometries are restricted to the following models - circular pattern 6/7, 18/19, 36/67 rods, with or without fillers. The fuel temperature distribution is not studied. The probability distribution of the statistical input is assumed to be a Gaussian function. The principle of random retrieval of statistical values is correct, but some additional correlations could be found from a more
Statistical analysis of the determinations of the Sun's Galactocentric distance
Malkin, Zinovy
2013-02-01
Based on several tens of R0 measurements made during the past two decades, several studies have been performed to derive the best estimate of R0. Some used just simple averaging to derive a result, whereas others provided comprehensive analyses of possible errors in published results. In either case, detailed statistical analyses of data used were not performed. However, a computation of the best estimates of the Galactic rotation constants is not only an astronomical but also a metrological task. Here we perform an analysis of 53 R0 measurements (published in the past 20 years) to assess the consistency of the data. Our analysis shows that they are internally consistent. It is also shown that any trend in the R0 estimates from the last 20 years is statistically negligible, which renders the presence of a bandwagon effect doubtful. On the other hand, the formal errors in the published R0 estimates improve significantly with time.
A statistical analysis of electrical cerebral activity
International Nuclear Information System (INIS)
Bassant, Marie-Helene
1971-01-01
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 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) [fr
Statistical analysis of ultrasonic measurements in concrete
Chiang, Chih-Hung; Chen, Po-Chih
2002-05-01
Stress wave techniques such as measurements of ultrasonic pulse velocity are often used to evaluate concrete quality in structures. For proper interpretation of measurement results, the dependence of pulse transit time on the average acoustic impedance and the material homogeneity along the sound path need to be examined. Semi-direct measurement of pulse velocity could be more convenient than through transmission measurement. It is not necessary to assess both sides of concrete floors or walls. A novel measurement scheme is proposed and verified based on statistical analysis. It is shown that Semi-direct measurements are very effective for gathering large amount of pulse velocity data from concrete reference specimens. The variability of measurements is comparable with that reported by American Concrete Institute using either break-off or pullout tests.
A κ-generalized statistical mechanics approach to income analysis
International Nuclear Information System (INIS)
Clementi, F; Gallegati, M; Kaniadakis, G
2009-01-01
This paper proposes a statistical mechanics approach to the analysis of income distribution and inequality. A new distribution function, having its roots in the framework of κ-generalized statistics, is derived that is particularly suitable for describing the whole spectrum of incomes, from the low–middle income region up to the high income Pareto power-law regime. Analytical expressions for the shape, moments and some other basic statistical properties are given. Furthermore, several well-known econometric tools for measuring inequality, which all exist in a closed form, are considered. A method for parameter estimation is also discussed. The model is shown to fit remarkably well the data on personal income for the United States, and the analysis of inequality performed in terms of its parameters is revealed as very powerful
A κ-generalized statistical mechanics approach to income analysis
Clementi, F.; Gallegati, M.; Kaniadakis, G.
2009-02-01
This paper proposes a statistical mechanics approach to the analysis of income distribution and inequality. A new distribution function, having its roots in the framework of κ-generalized statistics, is derived that is particularly suitable for describing the whole spectrum of incomes, from the low-middle income region up to the high income Pareto power-law regime. Analytical expressions for the shape, moments and some other basic statistical properties are given. Furthermore, several well-known econometric tools for measuring inequality, which all exist in a closed form, are considered. A method for parameter estimation is also discussed. The model is shown to fit remarkably well the data on personal income for the United States, and the analysis of inequality performed in terms of its parameters is revealed as very powerful.
On two methods of statistical image analysis
Missimer, J; Knorr, U; Maguire, RP; Herzog, H; Seitz, RJ; Tellman, L; Leenders, K.L.
1999-01-01
The computerized brain atlas (CBA) and statistical parametric mapping (SPM) are two procedures for voxel-based statistical evaluation of PET activation studies. Each includes spatial standardization of image volumes, computation of a statistic, and evaluation of its significance. In addition,
Analytical and statistical analysis of elemental composition of lichens
International Nuclear Information System (INIS)
Calvelo, S.; Baccala, N.; Bubach, D.; Arribere, M.A.; Riberio Guevara, S.
1997-01-01
The elemental composition of lichens from remote southern South America regions has been studied with analytical and statistical techniques to determine if the values obtained reflect species, growth forms or habitat characteristics. The enrichment factors are calculated discriminated by species and collection site and compared with data available in the literature. The elemental concentrations are standardized and compared for different species. The information was statistically processed, a cluster analysis was performed using the three first principal axes of the PCA; the three groups formed are presented. Their relationship with the species, collection sites and the lichen growth forms are interpreted. (author)
Application of descriptive statistics in analysis of experimental data
Mirilović Milorad; Pejin Ivana
2008-01-01
Statistics today represent a group of scientific methods for the quantitative and qualitative investigation of variations in mass appearances. In fact, statistics present a group of methods that are used for the accumulation, analysis, presentation and interpretation of data necessary for reaching certain conclusions. Statistical analysis is divided into descriptive statistical analysis and inferential statistics. The values which represent the results of an experiment, and which are the subj...
Lou, Qiqi; Wang, Yan; Wang, Zhaoqi; Liu, Yongji; Zhang, Lin; Fang, Hui
2015-09-01
Preoperative and postoperative wavefront aberrations of 73 myopic eyes with small incision lenticule extraction surgery are analyzed in this paper. Twenty-eight postoperative individual eye models are constructed to investigate the visual acuity (VA) of human eyes. Results show that in photopic condition, residual defocus, residual astigmatism, and higher-order aberrations are relatively small. 100% of eyes reach a VA of 0.8 or better, and 89.3% of eyes reach a VA of 1.0 or better. In scotopic condition, the residual defocus and the higher-order aberrations are, respectively, 1.9 and 8.5 times the amount of that in photopic condition, and the defocus becomes the main factor attenuating visual performance.
Banas, Krzysztof; Banas, Agnieszka; Gajda, Mariusz; Kwiatek, Wojciech M; Pawlicki, Bohdan; Breese, Mark B H
2014-07-15
Assessment of the performance and up-to-date diagnostics of scientific equipment is one of the key components in contemporary laboratories. Most reliable checks are performed by real test experiments while varying the experimental conditions (typically, in the case of infrared spectroscopic measurements, the size of the beam aperture, the duration of the experiment, the spectral range, the scanner velocity, etc.). On the other hand, the stability of the instrument response in time is another key element of the great value. Source stability (or easy predictable temporal changes, similar to those observed in the case of synchrotron radiation-based sources working in non top-up mode), detector stability (especially in the case of liquid nitrogen- or liquid helium-cooled detectors) should be monitored. In these cases, recorded datasets (spectra) include additional variables such as time stamp when a particular spectrum was recorded (in the case of time trial experiments). A favorable approach in evaluating these data is building hyperspectral object that consist of all spectra and all additional parameters at which these spectra were recorded. Taking into account that these datasets could be considerably large in size, there is a need for the tools for semiautomatic data evaluation and information extraction. A comprehensive R archive network--the open-source R Environment--with its flexibility and growing potential, fits these requirements nicely. In this paper, examples of practical implementation of methods available in R for real-life Fourier transform infrared (FTIR) spectroscopic data problems are presented. However, this approach could easily be adopted to many various laboratory scenarios with other spectroscopic techniques.
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.
Statistics Analysis Measures Painting of Cooling Tower
Directory of Open Access Journals (Sweden)
A. Zacharopoulou
2013-01-01
Full Text Available This study refers to the cooling tower of Megalopolis (construction 1975 and protection from corrosive environment. The maintenance of the cooling tower took place in 2008. The cooling tower was badly damaged from corrosion of reinforcement. The parabolic cooling towers (factory of electrical power are a typical example of construction, which has a special aggressive environment. The protection of cooling towers is usually achieved through organic coatings. Because of the different environmental impacts on the internal and external side of the cooling tower, a different system of paint application is required. The present study refers to the damages caused by corrosion process. The corrosive environments, the application of this painting, the quality control process, the measures and statistics analysis, and the results were discussed in this study. In the process of quality control the following measurements were taken into consideration: (1 examination of the adhesion with the cross-cut test, (2 examination of the film thickness, and (3 controlling of the pull-off resistance for concrete substrates and paintings. Finally, this study refers to the correlations of measurements, analysis of failures in relation to the quality of repair, and rehabilitation of the cooling tower. Also this study made a first attempt to apply the specific corrosion inhibitors in such a large structure.
State analysis of BOP using statistical and heuristic methods
International Nuclear Information System (INIS)
Heo, Gyun Young; Chang, Soon Heung
2003-01-01
Under the deregulation environment, the performance enhancement of BOP in nuclear power plants is being highlighted. To analyze performance level of BOP, we use the performance test procedures provided from an authorized institution such as ASME. However, through plant investigation, it was proved that the requirements of the performance test procedures about the reliability and quantity of sensors was difficult to be satisfied. As a solution of this, state analysis method that are the expanded concept of signal validation, was proposed on the basis of the statistical and heuristic approaches. Authors recommended the statistical linear regression model by analyzing correlation among BOP parameters as a reference state analysis method. Its advantage is that its derivation is not heuristic, it is possible to calculate model uncertainty, and it is easy to apply to an actual plant. The error of the statistical linear regression model is below 3% under normal as well as abnormal system states. Additionally a neural network model was recommended since the statistical model is impossible to apply to the validation of all of the sensors and is sensitive to the outlier that is the signal located out of a statistical distribution. Because there are a lot of sensors need to be validated in BOP, wavelet analysis (WA) were applied as a pre-processor for the reduction of input dimension and for the enhancement of training accuracy. The outlier localization capability of WA enhanced the robustness of the neural network. The trained neural network restored the degraded signals to the values within ±3% of the true signals
Transit safety & security statistics & analysis 2002 annual report (formerly SAMIS)
2004-12-01
The Transit Safety & Security Statistics & Analysis 2002 Annual Report (formerly SAMIS) is a compilation and analysis of mass transit accident, casualty, and crime statistics reported under the Federal Transit Administrations (FTAs) National Tr...
Transit safety & security statistics & analysis 2003 annual report (formerly SAMIS)
2005-12-01
The Transit Safety & Security Statistics & Analysis 2003 Annual Report (formerly SAMIS) is a compilation and analysis of mass transit accident, casualty, and crime statistics reported under the Federal Transit Administrations (FTAs) National Tr...
Statistical analysis of long term spatial and temporal trends of ...
Indian Academy of Sciences (India)
Statistical analysis of long term spatial and temporal trends of temperature ... CGCM3; HadCM3; modified Mann–Kendall test; statistical analysis; Sutlej basin. ... Water Resources Systems Division, National Institute of Hydrology, Roorkee 247 ...
Analysis of spectral data with rare events statistics
International Nuclear Information System (INIS)
Ilyushchenko, V.I.; Chernov, N.I.
1990-01-01
The case is considered of analyzing experimental data, when the results of individual experimental runs cannot be summed due to large systematic errors. A statistical analysis of the hypothesis about the persistent peaks in the spectra has been performed by means of the Neyman-Pearson test. The computations demonstrate the confidence level for the hypothesis about the presence of a persistent peak in the spectrum is proportional to the square root of the number of independent experimental runs, K. 5 refs
Statistical approach to partial equilibrium analysis
Wang, Yougui; Stanley, H. E.
2009-04-01
A statistical approach to market equilibrium and efficiency analysis is proposed in this paper. One factor that governs the exchange decisions of traders in a market, named willingness price, is highlighted and constitutes the whole theory. The supply and demand functions are formulated as the distributions of corresponding willing exchange over the willingness price. The laws of supply and demand can be derived directly from these distributions. The characteristics of excess demand function are analyzed and the necessary conditions for the existence and uniqueness of equilibrium point of the market are specified. The rationing rates of buyers and sellers are introduced to describe the ratio of realized exchange to willing exchange, and their dependence on the market price is studied in the cases of shortage and surplus. The realized market surplus, which is the criterion of market efficiency, can be written as a function of the distributions of willing exchange and the rationing rates. With this approach we can strictly prove that a market is efficient in the state of equilibrium.
Analysis of Variance: What Is Your Statistical Software Actually Doing?
Li, Jian; Lomax, Richard G.
2011-01-01
Users assume statistical software packages produce accurate results. In this article, the authors systematically examined Statistical Package for the Social Sciences (SPSS) and Statistical Analysis System (SAS) for 3 analysis of variance (ANOVA) designs, mixed-effects ANOVA, fixed-effects analysis of covariance (ANCOVA), and nested ANOVA. For each…
Fisher statistics for analysis of diffusion tensor directional information.
Hutchinson, Elizabeth B; Rutecki, Paul A; Alexander, Andrew L; Sutula, Thomas P
2012-04-30
A statistical approach is presented for the quantitative analysis of diffusion tensor imaging (DTI) directional information using Fisher statistics, which were originally developed for the analysis of vectors in the field of paleomagnetism. In this framework, descriptive and inferential statistics have been formulated based on the Fisher probability density function, a spherical analogue of the normal distribution. The Fisher approach was evaluated for investigation of rat brain DTI maps to characterize tissue orientation in the corpus callosum, fornix, and hilus of the dorsal hippocampal dentate gyrus, and to compare directional properties in these regions following status epilepticus (SE) or traumatic brain injury (TBI) with values in healthy brains. Direction vectors were determined for each region of interest (ROI) for each brain sample and Fisher statistics were applied to calculate the mean direction vector and variance parameters in the corpus callosum, fornix, and dentate gyrus of normal rats and rats that experienced TBI or SE. Hypothesis testing was performed by calculation of Watson's F-statistic and associated p-value giving the likelihood that grouped observations were from the same directional distribution. In the fornix and midline corpus callosum, no directional differences were detected between groups, however in the hilus, significant (pstatistical comparison of tissue structural orientation. Copyright © 2012 Elsevier B.V. All rights reserved.
HistFitter software framework for statistical data analysis
Energy Technology Data Exchange (ETDEWEB)
Baak, M. [CERN, Geneva (Switzerland); Besjes, G.J. [Radboud University Nijmegen, Nijmegen (Netherlands); Nikhef, Amsterdam (Netherlands); Cote, D. [University of Texas, Arlington (United States); Koutsman, A. [TRIUMF, Vancouver (Canada); Lorenz, J. [Ludwig-Maximilians-Universitaet Muenchen, Munich (Germany); Excellence Cluster Universe, Garching (Germany); Short, D. [University of Oxford, Oxford (United Kingdom)
2015-04-15
We present a software framework for statistical data analysis, called HistFitter, that has been used extensively by the ATLAS Collaboration to analyze big datasets originating from proton-proton collisions at the Large Hadron Collider at CERN. Since 2012 HistFitter has been the standard statistical tool in searches for supersymmetric particles performed by ATLAS. HistFitter is a programmable and flexible framework to build, book-keep, fit, interpret and present results of data models of nearly arbitrary complexity. Starting from an object-oriented configuration, defined by users, the framework builds probability density functions that are automatically fit to data and interpreted with statistical tests. Internally HistFitter uses the statistics packages RooStats and HistFactory. A key innovation of HistFitter is its design, which is rooted in analysis strategies of particle physics. The concepts of control, signal and validation regions are woven into its fabric. These are progressively treated with statistically rigorous built-in methods. Being capable of working with multiple models at once that describe the data, HistFitter introduces an additional level of abstraction that allows for easy bookkeeping, manipulation and testing of large collections of signal hypotheses. Finally, HistFitter provides a collection of tools to present results with publication quality style through a simple command-line interface. (orig.)
HistFitter software framework for statistical data analysis
International Nuclear Information System (INIS)
Baak, M.; Besjes, G.J.; Cote, D.; Koutsman, A.; Lorenz, J.; Short, D.
2015-01-01
We present a software framework for statistical data analysis, called HistFitter, that has been used extensively by the ATLAS Collaboration to analyze big datasets originating from proton-proton collisions at the Large Hadron Collider at CERN. Since 2012 HistFitter has been the standard statistical tool in searches for supersymmetric particles performed by ATLAS. HistFitter is a programmable and flexible framework to build, book-keep, fit, interpret and present results of data models of nearly arbitrary complexity. Starting from an object-oriented configuration, defined by users, the framework builds probability density functions that are automatically fit to data and interpreted with statistical tests. Internally HistFitter uses the statistics packages RooStats and HistFactory. A key innovation of HistFitter is its design, which is rooted in analysis strategies of particle physics. The concepts of control, signal and validation regions are woven into its fabric. These are progressively treated with statistically rigorous built-in methods. Being capable of working with multiple models at once that describe the data, HistFitter introduces an additional level of abstraction that allows for easy bookkeeping, manipulation and testing of large collections of signal hypotheses. Finally, HistFitter provides a collection of tools to present results with publication quality style through a simple command-line interface. (orig.)
Using Pre-Statistical Analysis to Streamline Monitoring Assessments
International Nuclear Information System (INIS)
Reed, J.K.
1999-01-01
A variety of statistical methods exist to aid evaluation of groundwater quality and subsequent decision making in regulatory programs. These methods are applied because of large temporal and spatial extrapolations commonly applied to these data. In short, statistical conclusions often serve as a surrogate for knowledge. However, facilities with mature monitoring programs that have generated abundant data have inherently less uncertainty because of the sheer quantity of analytical results. In these cases, statistical tests can be less important, and ''expert'' data analysis should assume an important screening role.The WSRC Environmental Protection Department, working with the General Separations Area BSRI Environmental Restoration project team has developed a method for an Integrated Hydrogeological Analysis (IHA) of historical water quality data from the F and H Seepage Basins groundwater remediation project. The IHA combines common sense analytical techniques and a GIS presentation that force direct interactive evaluation of the data. The IHA can perform multiple data analysis tasks required by the RCRA permit. These include: (1) Development of a groundwater quality baseline prior to remediation startup, (2) Targeting of constituents for removal from RCRA GWPS, (3) Targeting of constituents for removal from UIC, permit, (4) Targeting of constituents for reduced, (5)Targeting of monitoring wells not producing representative samples, (6) Reduction in statistical evaluation, and (7) Identification of contamination from other facilities
Time Series Analysis Based on Running Mann Whitney Z Statistics
A sensitive and objective time series analysis method based on the calculation of Mann Whitney U statistics is described. This method samples data rankings over moving time windows, converts those samples to Mann-Whitney U statistics, and then normalizes the U statistics to Z statistics using Monte-...
COMPARATIVE STATISTICAL ANALYSIS OF GENOTYPES’ COMBINING
Directory of Open Access Journals (Sweden)
V. Z. Stetsyuk
2015-05-01
The program provides the creation of desktop program complex for statistics calculations on a personal computer of doctor. Modern methods and tools for development of information systems were described to create program.
SAS and R data management, statistical analysis, and graphics
Kleinman, Ken
2009-01-01
An All-in-One Resource for Using SAS and R to Carry out Common TasksProvides a path between languages that is easier than reading complete documentationSAS and R: Data Management, Statistical Analysis, and Graphics presents an easy way to learn how to perform an analytical task in both SAS and R, without having to navigate through the extensive, idiosyncratic, and sometimes unwieldy software documentation. The book covers many common tasks, such as data management, descriptive summaries, inferential procedures, regression analysis, and the creation of graphics, along with more complex applicat
Directory of Open Access Journals (Sweden)
Sylvie Fortier
2005-06-01
Full Text Available The purpose of this study was twofold: (a to examine if kinetic and kinematic parameters of the sprint start could differentiate elite from sub-elite sprinters and, (b to investigate whether providing feedback (FB about selected parameters could improve starting block performance of intermediate sprinters over a 6-week training period. Twelve male sprinters, assigned to an elite or a sub-elite group, participated in Experiment 1. Eight intermediate sprinters participated in Experiment 2. All athletes were required to perform three sprint starts at maximum intensity followed by a 10-m run. To detect differences between elite and sub-elite groups, comparisons were made using t-tests for independent samples. Parameters reaching a significant group difference were retained for the linear discriminant analysis (LDA. The LDA yielded four discriminative kinetic parameters. Feedback about these selected parameters was given to sprinters in Experiment 2. For this experiment, data acquisition was divided into three periods. The first six sessions were without specific FB, whereas the following six sessions were enriched by kinetic FB. Finally, athletes underwent a retention session (without FB 4 weeks after the twelfth session. Even though differences were found in the time to front peak force, the time to rear peak force, and the front peak force in the retention session, the results of the present study showed that providing FB about selected kinetic parameters differentiating elite from sub-elite sprinters did not improve the starting block performance of intermediate sprinters
A statistical test for outlier identification in data envelopment analysis
Directory of Open Access Journals (Sweden)
Morteza Khodabin
2010-09-01
Full Text Available In the use of peer group data to assess individual, typical or best practice performance, the effective detection of outliers is critical for achieving useful results. In these ‘‘deterministic’’ frontier models, statistical theory is now mostly available. This paper deals with the statistical pared sample method and its capability of detecting outliers in data envelopment analysis. In the presented method, each observation is deleted from the sample once and the resulting linear program is solved, leading to a distribution of efficiency estimates. Based on the achieved distribution, a pared test is designed to identify the potential outlier(s. We illustrate the method through a real data set. The method could be used in a first step, as an exploratory data analysis, before using any frontier estimation.
Statistical analysis of first period of operation of FTU Tokamak
International Nuclear Information System (INIS)
Crisanti, F.; Apruzzese, G.; Frigione, D.; Kroegler, H.; Lovisetto, L.; Mazzitelli, G.; Podda, S.
1996-09-01
On the FTU Tokamak the plasma physics operations started on the 20/4/90. The first plasma had a plasma current Ip=0.75 MA for about a second. The experimental phase lasted until 7/7/94, when a long shut-down begun for installing the toroidal limiter in the inner side of the vacuum vessel. In these four years of operations plasma experiments have been successfully exploited, e.g. experiments of single and multiple pellet injections; full current drive up to Ip=300 KA was obtained by using waves at the frequency of the Lower Hybrid; analysis of ohmic plasma parameters with different materials (from the low Z silicon to high Z tungsten) as plasma facing element was performed. In this work a statistical analysis of the full period of operation is presented. Moreover, a comparison with the statistical data from other Tokamaks is attempted
The CEO performance effect : Statistical issues and a complex fit perspective
Blettner, D.P.; Chaddad, F.R.; Bettis, R.
2012-01-01
How CEOs affect strategy and performance is important to strategic management research. We show that sophisticated statistical analysis alone is problematic for establishing the magnitude and causes of CEO impact on performance. We discuss three problem areas that substantially distort the
Feature-Based Statistical Analysis of Combustion Simulation Data
Energy Technology Data Exchange (ETDEWEB)
Bennett, J; Krishnamoorthy, V; Liu, S; Grout, R; Hawkes, E; Chen, J; Pascucci, V; Bremer, P T
2011-11-18
We present a new framework for feature-based statistical analysis of large-scale scientific data and demonstrate its effectiveness by analyzing features from Direct Numerical Simulations (DNS) of turbulent combustion. Turbulent flows are ubiquitous and account for transport and mixing processes in combustion, astrophysics, fusion, and climate modeling among other disciplines. They are also characterized by coherent structure or organized motion, i.e. nonlocal entities whose geometrical features can directly impact molecular mixing and reactive processes. While traditional multi-point statistics provide correlative information, they lack nonlocal structural information, and hence, fail to provide mechanistic causality information between organized fluid motion and mixing and reactive processes. Hence, it is of great interest to capture and track flow features and their statistics together with their correlation with relevant scalar quantities, e.g. temperature or species concentrations. In our approach we encode the set of all possible flow features by pre-computing merge trees augmented with attributes, such as statistical moments of various scalar fields, e.g. temperature, as well as length-scales computed via spectral analysis. The computation is performed in an efficient streaming manner in a pre-processing step and results in a collection of meta-data that is orders of magnitude smaller than the original simulation data. This meta-data is sufficient to support a fully flexible and interactive analysis of the features, allowing for arbitrary thresholds, providing per-feature statistics, and creating various global diagnostics such as Cumulative Density Functions (CDFs), histograms, or time-series. We combine the analysis with a rendering of the features in a linked-view browser that enables scientists to interactively explore, visualize, and analyze the equivalent of one terabyte of simulation data. We highlight the utility of this new framework for combustion
Perceptual and statistical analysis of cardiac phase and amplitude images
International Nuclear Information System (INIS)
Houston, A.; Craig, A.
1991-01-01
A perceptual experiment was conducted using cardiac phase and amplitude images. Estimates of statistical parameters were derived from the images and the diagnostic potential of human and statistical decisions compared. Five methods were used to generate the images from 75 gated cardiac studies, 39 of which were classified as pathological. The images were presented to 12 observers experienced in nuclear medicine. The observers rated the images using a five-category scale based on their confidence of an abnormality presenting. Circular and linear statistics were used to analyse phase and amplitude image data, respectively. Estimates of mean, standard deviation (SD), skewness, kurtosis and the first term of the spatial correlation function were evaluated in the region of the left ventricle. A receiver operating characteristic analysis was performed on both sets of data and the human and statistical decisions compared. For phase images, circular SD was shown to discriminate better between normal and abnormal than experienced observers, but no single statistic discriminated as well as the human observer for amplitude images. (orig.)
Statistical Analysis of Research Data | Center for Cancer Research
Recent advances in cancer biology have resulted in the need for increased statistical analysis of research data. The Statistical Analysis of Research Data (SARD) course will be held on April 5-6, 2018 from 9 a.m.-5 p.m. at the National Institutes of Health's Natcher Conference Center, Balcony C on the Bethesda Campus. SARD is designed to provide an overview on the general principles of statistical analysis of research data. The first day will feature univariate data analysis, including descriptive statistics, probability distributions, one- and two-sample inferential statistics.
Software for statistical data analysis used in Higgs searches
International Nuclear Information System (INIS)
Gumpert, Christian; Moneta, Lorenzo; Cranmer, Kyle; Kreiss, Sven; Verkerke, Wouter
2014-01-01
The analysis and interpretation of data collected by the Large Hadron Collider (LHC) requires advanced statistical tools in order to quantify the agreement between observation and theoretical models. RooStats is a project providing a statistical framework for data analysis with the focus on discoveries, confidence intervals and combination of different measurements in both Bayesian and frequentist approaches. It employs the RooFit data modelling language where mathematical concepts such as variables, (probability density) functions and integrals are represented as C++ objects. RooStats and RooFit rely on the persistency technology of the ROOT framework. The usage of a common data format enables the concept of digital publishing of complicated likelihood functions. The statistical tools have been developed in close collaboration with the LHC experiments to ensure their applicability to real-life use cases. Numerous physics results have been produced using the RooStats tools, with the discovery of the Higgs boson by the ATLAS and CMS experiments being certainly the most popular among them. We will discuss tools currently used by LHC experiments to set exclusion limits, to derive confidence intervals and to estimate discovery significances based on frequentist statistics and the asymptotic behaviour of likelihood functions. Furthermore, new developments in RooStats and performance optimisation necessary to cope with complex models depending on more than 1000 variables will be reviewed
Statistical network analysis for analyzing policy networks
DEFF Research Database (Denmark)
Robins, Garry; Lewis, Jenny; Wang, Peng
2012-01-01
and policy network methodology is the development of statistical modeling approaches that can accommodate such dependent data. In this article, we review three network statistical methods commonly used in the current literature: quadratic assignment procedures, exponential random graph models (ERGMs......To analyze social network data using standard statistical approaches is to risk incorrect inference. The dependencies among observations implied in a network conceptualization undermine standard assumptions of the usual general linear models. One of the most quickly expanding areas of social......), and stochastic actor-oriented models. We focus most attention on ERGMs by providing an illustrative example of a model for a strategic information network within a local government. We draw inferences about the structural role played by individuals recognized as key innovators and conclude that such an approach...
International Nuclear Information System (INIS)
Samatova, Nagiza F; Branstetter, Marcia; Ganguly, Auroop R; Hettich, Robert; Khan, Shiraj; Kora, Guruprasad; Li, Jiangtian; Ma, Xiaosong; Pan, Chongle; Shoshani, Arie; Yoginath, Srikanth
2006-01-01
Ultrascale computing and high-throughput experimental technologies have enabled the production of scientific data about complex natural phenomena. With this opportunity, comes a new problem - the massive quantities of data so produced. Answers to fundamental questions about the nature of those phenomena remain largely hidden in the produced data. The goal of this work is to provide a scalable high performance statistical data analysis framework to help scientists perform interactive analyses of these raw data to extract knowledge. Towards this goal we have been developing an open source parallel statistical analysis package, called Parallel R, that lets scientists employ a wide range of statistical analysis routines on high performance shared and distributed memory architectures without having to deal with the intricacies of parallelizing these routines
Statistical performance evaluation of ECG transmission using wireless networks.
Shakhatreh, Walid; Gharaibeh, Khaled; Al-Zaben, Awad
2013-07-01
This paper presents simulation of the transmission of biomedical signals (using ECG signal as an example) over wireless networks. Investigation of the effect of channel impairments including SNR, pathloss exponent, path delay and network impairments such as packet loss probability; on the diagnosability of the received ECG signal are presented. The ECG signal is transmitted through a wireless network system composed of two communication protocols; an 802.15.4- ZigBee protocol and an 802.11b protocol. The performance of the transmission is evaluated using higher order statistics parameters such as kurtosis and Negative Entropy in addition to the common techniques such as the PRD, RMS and Cross Correlation.
Statistical models and methods for reliability and survival analysis
Couallier, Vincent; Huber-Carol, Catherine; Mesbah, Mounir; Huber -Carol, Catherine; Limnios, Nikolaos; Gerville-Reache, Leo
2013-01-01
Statistical Models and Methods for Reliability and Survival Analysis brings together contributions by specialists in statistical theory as they discuss their applications providing up-to-date developments in methods used in survival analysis, statistical goodness of fit, stochastic processes for system reliability, amongst others. Many of these are related to the work of Professor M. Nikulin in statistics over the past 30 years. The authors gather together various contributions with a broad array of techniques and results, divided into three parts - Statistical Models and Methods, Statistical
SMART performance analysis methodology
International Nuclear Information System (INIS)
Lim, H. S.; Kim, H. C.; Lee, D. J.
2001-04-01
To ensure the required and desired operation over the plant lifetime, the performance analysis for the SMART NSSS design is done by means of the specified analysis methodologies for the performance related design basis events(PRDBE). The PRDBE is an occurrence(event) that shall be accommodated in the design of the plant and whose consequence would be no more severe than normal service effects of the plant equipment. The performance analysis methodology which systematizes the methods and procedures to analyze the PRDBEs is as follows. Based on the operation mode suitable to the characteristics of the SMART NSSS, the corresponding PRDBEs and allowable range of process parameters for these events are deduced. With the developed control logic for each operation mode, the system thermalhydraulics are analyzed for the chosen PRDBEs using the system analysis code. Particularly, because of different system characteristics of SMART from the existing commercial nuclear power plants, the operation mode, PRDBEs, control logic, and analysis code should be consistent with the SMART design. This report presents the categories of the PRDBEs chosen based on each operation mode and the transition among these and the acceptance criteria for each PRDBE. It also includes the analysis methods and procedures for each PRDBE and the concept of the control logic for each operation mode. Therefore this report in which the overall details for SMART performance analysis are specified based on the current SMART design, would be utilized as a guide for the detailed performance analysis
Statistical analysis of hydrodynamic cavitation events
Gimenez, G.; Sommer, R.
1980-10-01
The frequency (number of events per unit time) of pressure pulses produced by hydrodynamic cavitation bubble collapses is investigated using statistical methods. The results indicate that this frequency is distributed according to a normal law, its parameters not being time-evolving.
Statistical analysis of lineaments of Goa, India
Digital Repository Service at National Institute of Oceanography (India)
Iyer, S.D.; Banerjee, G.; Wagle, B.G.
statistically to obtain the nonlinear pattern in the form of a cosine wave. Three distinct peaks were found at azimuths of 40-45 degrees, 90-95 degrees and 140-145 degrees, which have peak values of 5.85, 6.80 respectively. These three peaks are correlated...
On statistical analysis of compound point process
Czech Academy of Sciences Publication Activity Database
Volf, Petr
2006-01-01
Roč. 35, 2-3 (2006), s. 389-396 ISSN 1026-597X R&D Projects: GA ČR(CZ) GA402/04/1294 Institutional research plan: CEZ:AV0Z10750506 Keywords : counting process * compound process * hazard function * Cox -model Subject RIV: BB - Applied Statistics, Operational Research
Statistical Analysis Of Reconnaissance Geochemical Data From ...
African Journals Online (AJOL)
, Co, Mo, Hg, Sb, Tl, Sc, Cr, Ni, La, W, V, U, Th, Bi, Sr and Ga in 56 stream sediment samples collected from Orle drainage system were subjected to univariate and multivariate statistical analyses. The univariate methods used include ...
Statistical analysis of medical data using SAS
Der, Geoff
2005-01-01
An Introduction to SASDescribing and Summarizing DataBasic InferenceScatterplots Correlation: Simple Regression and SmoothingAnalysis of Variance and CovarianceMultiple RegressionLogistic RegressionThe Generalized Linear ModelGeneralized Additive ModelsNonlinear Regression ModelsThe Analysis of Longitudinal Data IThe Analysis of Longitudinal Data II: Models for Normal Response VariablesThe Analysis of Longitudinal Data III: Non-Normal ResponseSurvival AnalysisAnalysis Multivariate Date: Principal Components and Cluster AnalysisReferences
Precision Statistical Analysis of Images Based on Brightness Distribution
Directory of Open Access Journals (Sweden)
Muzhir Shaban Al-Ani
2017-07-01
Full Text Available Study the content of images is considered an important topic in which reasonable and accurate analysis of images are generated. Recently image analysis becomes a vital field because of huge number of images transferred via transmission media in our daily life. These crowded media with images lead to highlight in research area of image analysis. In this paper, the implemented system is passed into many steps to perform the statistical measures of standard deviation and mean values of both color and grey images. Whereas the last step of the proposed method concerns to compare the obtained results in different cases of the test phase. In this paper, the statistical parameters are implemented to characterize the content of an image and its texture. Standard deviation, mean and correlation values are used to study the intensity distribution of the tested images. Reasonable results are obtained for both standard deviation and mean value via the implementation of the system. The major issue addressed in the work is concentrated on brightness distribution via statistical measures applying different types of lighting.
2012-09-01
Services FSD Federated Services Daemon I&A Identification and Authentication IKE Internet Key Exchange KPI Key Performance Indicator LAN Local Area...spection takes place in different processes in the server architecture. Key Performance Indica- tor ( KPI )s associated with the system need to be...application and risk analysis of security controls. Thus, measurement of the KPIs is needed before an informed tradeoff between the performance penalties
Fundamentals of statistical experimental design and analysis
Easterling, Robert G
2015-01-01
Professionals in all areas - business; government; the physical, life, and social sciences; engineering; medicine, etc. - benefit from using statistical experimental design to better understand their worlds and then use that understanding to improve the products, processes, and programs they are responsible for. This book aims to provide the practitioners of tomorrow with a memorable, easy to read, engaging guide to statistics and experimental design. This book uses examples, drawn from a variety of established texts, and embeds them in a business or scientific context, seasoned with a dash of humor, to emphasize the issues and ideas that led to the experiment and the what-do-we-do-next? steps after the experiment. Graphical data displays are emphasized as means of discovery and communication and formulas are minimized, with a focus on interpreting the results that software produce. The role of subject-matter knowledge, and passion, is also illustrated. The examples do not require specialized knowledge, and t...
Common misconceptions about data analysis and statistics.
Motulsky, Harvey J
2014-11-01
Ideally, any experienced investigator with the right tools should be able to reproduce a finding published in a peer-reviewed biomedical science journal. In fact, the reproducibility of a large percentage of published findings has been questioned. Undoubtedly, there are many reasons for this, but one reason maybe that investigators fool themselves due to a poor understanding of statistical concepts. In particular, investigators often make these mistakes: 1. P-Hacking. This is when you reanalyze a data set in many different ways, or perhaps reanalyze with additional replicates, until you get the result you want. 2. Overemphasis on P values rather than on the actual size of the observed effect. 3. Overuse of statistical hypothesis testing, and being seduced by the word "significant". 4. Overreliance on standard errors, which are often misunderstood.
Common misconceptions about data analysis and statistics.
Motulsky, Harvey J
2015-02-01
Ideally, any experienced investigator with the right tools should be able to reproduce a finding published in a peer-reviewed biomedical science journal. In fact, the reproducibility of a large percentage of published findings has been questioned. Undoubtedly, there are many reasons for this, but one reason may be that investigators fool themselves due to a poor understanding of statistical concepts. In particular, investigators often make these mistakes: (1) P-Hacking. This is when you reanalyze a data set in many different ways, or perhaps reanalyze with additional replicates, until you get the result you want. (2) Overemphasis on P values rather than on the actual size of the observed effect. (3) Overuse of statistical hypothesis testing, and being seduced by the word "significant". (4) Overreliance on standard errors, which are often misunderstood.
Statistical analysis of radioactivity in the environment
International Nuclear Information System (INIS)
Barnes, M.G.; Giacomini, J.J.
1980-05-01
The pattern of radioactivity in surface soils of Area 5 of the Nevada Test Site is analyzed statistically by means of kriging. The 1962 event code-named Smallboy effected the greatest proportion of the area sampled, but some of the area was also affected by a number of other events. The data for this study were collected on a regular grid to take advantage of the efficiency of grid sampling
Critical analysis of adsorption data statistically
Kaushal, Achla; Singh, S. K.
2017-10-01
Experimental data can be presented, computed, and critically analysed in a different way using statistics. A variety of statistical tests are used to make decisions about the significance and validity of the experimental data. In the present study, adsorption was carried out to remove zinc ions from contaminated aqueous solution using mango leaf powder. The experimental data was analysed statistically by hypothesis testing applying t test, paired t test and Chi-square test to (a) test the optimum value of the process pH, (b) verify the success of experiment and (c) study the effect of adsorbent dose in zinc ion removal from aqueous solutions. Comparison of calculated and tabulated values of t and χ 2 showed the results in favour of the data collected from the experiment and this has been shown on probability charts. K value for Langmuir isotherm was 0.8582 and m value for Freundlich adsorption isotherm obtained was 0.725, both are mango leaf powder.
Statistical methods for data analysis in particle physics
AUTHOR|(CDS)2070643
2015-01-01
This concise set of course-based notes provides the reader with the main concepts and tools to perform statistical analysis of experimental data, in particular in the field of high-energy physics (HEP). First, an introduction to probability theory and basic statistics is given, mainly as reminder from advanced undergraduate studies, yet also in view to clearly distinguish the Frequentist versus Bayesian approaches and interpretations in subsequent applications. More advanced concepts and applications are gradually introduced, culminating in the chapter on upper limits as many applications in HEP concern hypothesis testing, where often the main goal is to provide better and better limits so as to be able to distinguish eventually between competing hypotheses or to rule out some of them altogether. Many worked examples will help newcomers to the field and graduate students to understand the pitfalls in applying theoretical concepts to actual data
Directory of Open Access Journals (Sweden)
Priya Ranganathan
2015-01-01
Full Text Available In the second part of a series on pitfalls in statistical analysis, we look at various ways in which a statistically significant study result can be expressed. We debunk some of the myths regarding the ′P′ value, explain the importance of ′confidence intervals′ and clarify the importance of including both values in a paper
Ranganathan, Priya; Pramesh, C. S.; Buyse, Marc
2015-01-01
In the second part of a series on pitfalls in statistical analysis, we look at various ways in which a statistically significant study result can be expressed. We debunk some of the myths regarding the ‘P’ value, explain the importance of ‘confidence intervals’ and clarify the importance of including both values in a paper PMID:25878958
Tuuli, Methodius G; Odibo, Anthony O
2011-08-01
The objective of this article is to discuss the rationale for common statistical tests used for the analysis and interpretation of prenatal diagnostic imaging studies. Examples from the literature are used to illustrate descriptive and inferential statistics. The uses and limitations of linear and logistic regression analyses are discussed in detail.
Using R for Data Management, Statistical Analysis, and Graphics
Horton, Nicholas J
2010-01-01
This title offers quick and easy access to key element of documentation. It includes worked examples across a wide variety of applications, tasks, and graphics. "Using R for Data Management, Statistical Analysis, and Graphics" presents an easy way to learn how to perform an analytical task in R, without having to navigate through the extensive, idiosyncratic, and sometimes unwieldy software documentation and vast number of add-on packages. Organized by short, clear descriptive entries, the book covers many common tasks, such as data management, descriptive summaries, inferential proc
Statistical Control Charts: Performances of Short Term Stock Trading in Croatia
Directory of Open Access Journals (Sweden)
Dumičić Ksenija
2015-03-01
Full Text Available Background: The stock exchange, as a regulated financial market, in modern economies reflects their economic development level. The stock market indicates the mood of investors in the development of a country and is an important ingredient for growth. Objectives: This paper aims to introduce an additional statistical tool used to support the decision-making process in stock trading, and it investigate the usage of statistical process control (SPC methods into the stock trading process. Methods/Approach: The individual (I, exponentially weighted moving average (EWMA and cumulative sum (CUSUM control charts were used for gaining trade signals. The open and the average prices of CROBEX10 index stocks on the Zagreb Stock Exchange were used in the analysis. The statistical control charts capabilities for stock trading in the short-run were analysed. Results: The statistical control chart analysis pointed out too many signals to buy or sell stocks. Most of them are considered as false alarms. So, the statistical control charts showed to be not so much useful in stock trading or in a portfolio analysis. Conclusions: The presence of non-normality and autocorellation has great impact on statistical control charts performances. It is assumed that if these two problems are solved, the use of statistical control charts in a portfolio analysis could be greatly improved.
Magnetic resonance imaging of the wrist: Diagnostic performance statistics
International Nuclear Information System (INIS)
Hobby, Jonathan L.; Tom, Brian D.M.; Bearcroft, Philip W.P.; Dixon, Adrian K.
2001-01-01
AIM: To review the published diagnostic performance statistics for magnetic resonance imaging (MRI) of the wrist for tears of the triangular fibrocartilage complex, the intrinsic carpal ligaments, and for osteonecrosis of the carpal bones. MATERIALS AND METHODS: We used Medline and Embase to search the English language literature. Studies evaluating the diagnostic performance of MRI of the wrist in living patients with surgical confirmation of MR findings were identified. RESULTS: We identified 11 studies reporting the diagnostic performance of MRI for tears of the triangular fibrocartilage complex for a total of 410 patients, six studies for the scapho-lunate ligament (159 patients), six studies for the luno-triquetral ligament (142 patients) and four studies (56 patients) for osteonecrosis of the carpal bones. CONCLUSIONS: Magnetic resonance imaging is an accurate means of diagnosing tears of the triangular fibrocartilage and carpal osteonecrosis. Although MRI is highly specific for tears of the intrinsic carpal ligaments, its sensitivity is low. The diagnostic performance of MRI in the wrist is improved by using high-resolution T2* weighted 3D gradient echo sequences. Using current imaging techniques without intra-articular contrast medium, magnetic resonance imaging cannot reliably exclude tears of the intrinsic carpal ligaments. Hobby, J.L. (2001)
Statistical learning methods in high-energy and astrophysics analysis
Energy Technology Data Exchange (ETDEWEB)
Zimmermann, J. [Forschungszentrum Juelich GmbH, Zentrallabor fuer Elektronik, 52425 Juelich (Germany) and Max-Planck-Institut fuer Physik, Foehringer Ring 6, 80805 Munich (Germany)]. E-mail: zimmerm@mppmu.mpg.de; Kiesling, C. [Max-Planck-Institut fuer Physik, Foehringer Ring 6, 80805 Munich (Germany)
2004-11-21
We discuss several popular statistical learning methods used in high-energy- and astro-physics analysis. After a short motivation for statistical learning we present the most popular algorithms and discuss several examples from current research in particle- and astro-physics. The statistical learning methods are compared with each other and with standard methods for the respective application.
Statistical learning methods in high-energy and astrophysics analysis
International Nuclear Information System (INIS)
Zimmermann, J.; Kiesling, C.
2004-01-01
We discuss several popular statistical learning methods used in high-energy- and astro-physics analysis. After a short motivation for statistical learning we present the most popular algorithms and discuss several examples from current research in particle- and astro-physics. The statistical learning methods are compared with each other and with standard methods for the respective application
Statistical analysis of partial reduced width distributions
International Nuclear Information System (INIS)
Tran Quoc Thuong.
1973-01-01
The aim of this study was to develop rigorous methods for analysing experimental event distributions according to a law in chi 2 and to check if the number of degrees of freedom ν is compatible with the value 1 for the reduced neutron width distribution. Two statistical methods were used (the maximum-likelihood method and the method of moments); it was shown, in a few particular cases, that ν is compatible with 1. The difference between ν and 1, if it exists, should not exceed 3%. These results confirm the validity of the compound nucleus model [fr
Statistical analysis of random duration times
International Nuclear Information System (INIS)
Engelhardt, M.E.
1996-04-01
This report presents basic statistical methods for analyzing data obtained by observing random time durations. It gives nonparametric estimates of the cumulative distribution function, reliability function and cumulative hazard function. These results can be applied with either complete or censored data. Several models which are commonly used with time data are discussed, and methods for model checking and goodness-of-fit tests are discussed. Maximum likelihood estimates and confidence limits are given for the various models considered. Some results for situations where repeated durations such as repairable systems are also discussed
Statistical analysis of random pulse trains
International Nuclear Information System (INIS)
Da Costa, G.
1977-02-01
Some experimental and theoretical results concerning the statistical properties of optical beams formed by a finite number of independent pulses are presented. The considered waves (corresponding to each pulse) present important spatial variations of the illumination distribution in a cross-section of the beam, due to the time-varying random refractive index distribution in the active medium. Some examples of this kind of emission are: (a) Free-running ruby laser emission; (b) Mode-locked pulse trains; (c) Randomly excited nonlinear media
Comparing Visual and Statistical Analysis of Multiple Baseline Design Graphs.
Wolfe, Katie; Dickenson, Tammiee S; Miller, Bridget; McGrath, Kathleen V
2018-04-01
A growing number of statistical analyses are being developed for single-case research. One important factor in evaluating these methods is the extent to which each corresponds to visual analysis. Few studies have compared statistical and visual analysis, and information about more recently developed statistics is scarce. Therefore, our purpose was to evaluate the agreement between visual analysis and four statistical analyses: improvement rate difference (IRD); Tau-U; Hedges, Pustejovsky, Shadish (HPS) effect size; and between-case standardized mean difference (BC-SMD). Results indicate that IRD and BC-SMD had the strongest overall agreement with visual analysis. Although Tau-U had strong agreement with visual analysis on raw values, it had poorer agreement when those values were dichotomized to represent the presence or absence of a functional relation. Overall, visual analysis appeared to be more conservative than statistical analysis, but further research is needed to evaluate the nature of these disagreements.
Data and statistical methods for analysis of trends and patterns
International Nuclear Information System (INIS)
Atwood, C.L.; Gentillon, C.D.; Wilson, G.E.
1992-11-01
This report summarizes topics considered at a working meeting on data and statistical methods for analysis of trends and patterns in US commercial nuclear power plants. This meeting was sponsored by the Office of Analysis and Evaluation of Operational Data (AEOD) of the Nuclear Regulatory Commission (NRC). Three data sets are briefly described: Nuclear Plant Reliability Data System (NPRDS), Licensee Event Report (LER) data, and Performance Indicator data. Two types of study are emphasized: screening studies, to see if any trends or patterns appear to be present; and detailed studies, which are more concerned with checking the analysis assumptions, modeling any patterns that are present, and searching for causes. A prescription is given for a screening study, and ideas are suggested for a detailed study, when the data take of any of three forms: counts of events per time, counts of events per demand, and non-event data
STATISTICS. The reusable holdout: Preserving validity in adaptive data analysis.
Dwork, Cynthia; Feldman, Vitaly; Hardt, Moritz; Pitassi, Toniann; Reingold, Omer; Roth, Aaron
2015-08-07
Misapplication of statistical data analysis is a common cause of spurious discoveries in scientific research. Existing approaches to ensuring the validity of inferences drawn from data assume a fixed procedure to be performed, selected before the data are examined. In common practice, however, data analysis is an intrinsically adaptive process, with new analyses generated on the basis of data exploration, as well as the results of previous analyses on the same data. We demonstrate a new approach for addressing the challenges of adaptivity based on insights from privacy-preserving data analysis. As an application, we show how to safely reuse a holdout data set many times to validate the results of adaptively chosen analyses. Copyright © 2015, American Association for the Advancement of Science.
CONFIDENCE LEVELS AND/VS. STATISTICAL HYPOTHESIS TESTING IN STATISTICAL ANALYSIS. CASE STUDY
Directory of Open Access Journals (Sweden)
ILEANA BRUDIU
2009-05-01
Full Text Available Estimated parameters with confidence intervals and testing statistical assumptions used in statistical analysis to obtain conclusions on research from a sample extracted from the population. Paper to the case study presented aims to highlight the importance of volume of sample taken in the study and how this reflects on the results obtained when using confidence intervals and testing for pregnant. If statistical testing hypotheses not only give an answer "yes" or "no" to some questions of statistical estimation using statistical confidence intervals provides more information than a test statistic, show high degree of uncertainty arising from small samples and findings build in the "marginally significant" or "almost significant (p very close to 0.05.
Bayesian Sensitivity Analysis of Statistical Models with Missing Data.
Zhu, Hongtu; Ibrahim, Joseph G; Tang, Niansheng
2014-04-01
Methods for handling missing data depend strongly on the mechanism that generated the missing values, such as missing completely at random (MCAR) or missing at random (MAR), as well as other distributional and modeling assumptions at various stages. It is well known that the resulting estimates and tests may be sensitive to these assumptions as well as to outlying observations. In this paper, we introduce various perturbations to modeling assumptions and individual observations, and then develop a formal sensitivity analysis to assess these perturbations in the Bayesian analysis of statistical models with missing data. We develop a geometric framework, called the Bayesian perturbation manifold, to characterize the intrinsic structure of these perturbations. We propose several intrinsic influence measures to perform sensitivity analysis and quantify the effect of various perturbations to statistical models. We use the proposed sensitivity analysis procedure to systematically investigate the tenability of the non-ignorable missing at random (NMAR) assumption. Simulation studies are conducted to evaluate our methods, and a dataset is analyzed to illustrate the use of our diagnostic measures.
Statistical models for competing risk analysis
International Nuclear Information System (INIS)
Sather, H.N.
1976-08-01
Research results on three new models for potential applications in competing risks problems. One section covers the basic statistical relationships underlying the subsequent competing risks model development. Another discusses the problem of comparing cause-specific risk structure by competing risks theory in two homogeneous populations, P1 and P2. Weibull models which allow more generality than the Berkson and Elveback models are studied for the effect of time on the hazard function. The use of concomitant information for modeling single-risk survival is extended to the multiple failure mode domain of competing risks. The model used to illustrate the use of this methodology is a life table model which has constant hazards within pre-designated intervals of the time scale. Two parametric models for bivariate dependent competing risks, which provide interesting alternatives, are proposed and examined
Statistical analysis of the ASME KIc database
International Nuclear Information System (INIS)
Sokolov, M.A.
1998-01-01
The American Society of Mechanical Engineers (ASME) K Ic curve is a function of test temperature (T) normalized to a reference nil-ductility temperature, RT NDT , namely, T-RT NDT . It was constructed as the lower boundary to the available K Ic database. Being a lower bound to the unique but limited database, the ASME K Ic curve concept does not discuss probability matters. However, a continuing evolution of fracture mechanics advances has led to employment of the Weibull distribution function to model the scatter of fracture toughness values in the transition range. The Weibull statistic/master curve approach was applied to analyze the current ASME K Ic database. It is shown that the Weibull distribution function models the scatter in K Ic data from different materials very well, while the temperature dependence is described by the master curve. Probabilistic-based tolerance-bound curves are suggested to describe lower-bound K Ic values
Statistical analysis of earthquake ground motion parameters
International Nuclear Information System (INIS)
1979-12-01
Several earthquake ground response parameters that define the strength, duration, and frequency content of the motions are investigated using regression analyses techniques; these techniques incorporate statistical significance testing to establish the terms in the regression equations. The parameters investigated are the peak acceleration, velocity, and displacement; Arias intensity; spectrum intensity; bracketed duration; Trifunac-Brady duration; and response spectral amplitudes. The study provides insight into how these parameters are affected by magnitude, epicentral distance, local site conditions, direction of motion (i.e., whether horizontal or vertical), and earthquake event type. The results are presented in a form so as to facilitate their use in the development of seismic input criteria for nuclear plants and other major structures. They are also compared with results from prior investigations that have been used in the past in the criteria development for such facilities
Humans make efficient use of natural image statistics when performing spatial interpolation.
D'Antona, Anthony D; Perry, Jeffrey S; Geisler, Wilson S
2013-12-16
Visual systems learn through evolution and experience over the lifespan to exploit the statistical structure of natural images when performing visual tasks. Understanding which aspects of this statistical structure are incorporated into the human nervous system is a fundamental goal in vision science. To address this goal, we measured human ability to estimate the intensity of missing image pixels in natural images. Human estimation accuracy is compared with various simple heuristics (e.g., local mean) and with optimal observers that have nearly complete knowledge of the local statistical structure of natural images. Human estimates are more accurate than those of simple heuristics, and they match the performance of an optimal observer that knows the local statistical structure of relative intensities (contrasts). This optimal observer predicts the detailed pattern of human estimation errors and hence the results place strong constraints on the underlying neural mechanisms. However, humans do not reach the performance of an optimal observer that knows the local statistical structure of the absolute intensities, which reflect both local relative intensities and local mean intensity. As predicted from a statistical analysis of natural images, human estimation accuracy is negligibly improved by expanding the context from a local patch to the whole image. Our results demonstrate that the human visual system exploits efficiently the statistical structure of natural images.
Statistical power analysis for the behavioral sciences
National Research Council Canada - National Science Library
Cohen, Jacob
1988-01-01
.... A chapter has been added for power analysis in set correlation and multivariate methods (Chapter 10). Set correlation is a realization of the multivariate general linear model, and incorporates the standard multivariate methods...
Statistical power analysis for the behavioral sciences
National Research Council Canada - National Science Library
Cohen, Jacob
1988-01-01
... offers a unifying framework and some new data-analytic possibilities. 2. A new chapter (Chapter 11) considers some general topics in power analysis in more integrted form than is possible in the earlier...
Statistical methods for categorical data analysis
Powers, Daniel
2008-01-01
This book provides a comprehensive introduction to methods and models for categorical data analysis and their applications in social science research. Companion website also available, at https://webspace.utexas.edu/dpowers/www/
Statistical Modelling of Wind Proles - Data Analysis and Modelling
DEFF Research Database (Denmark)
Jónsson, Tryggvi; Pinson, Pierre
The aim of the analysis presented in this document is to investigate whether statistical models can be used to make very short-term predictions of wind profiles.......The aim of the analysis presented in this document is to investigate whether statistical models can be used to make very short-term predictions of wind profiles....
Sensitivity analysis of ranked data: from order statistics to quantiles
Heidergott, B.F.; Volk-Makarewicz, W.
2015-01-01
In this paper we provide the mathematical theory for sensitivity analysis of order statistics of continuous random variables, where the sensitivity is with respect to a distributional parameter. Sensitivity analysis of order statistics over a finite number of observations is discussed before
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
Use of statistical process control in evaluation of academic performance
Directory of Open Access Journals (Sweden)
Ezequiel Gibbon Gautério
2014-05-01
Full Text Available The aim of this article was to study some indicators of academic performance (number of students per class, dropout rate, failure rate and scores obtained by the students to identify a pattern of behavior that would enable to implement improvements in the teaching-learning process. The sample was composed of five classes of undergraduate courses in Engineering. The data were collected for three years. Initially an exploratory analysis with analytical and graphical techniques was performed. An analysis of variance and Tukey’s test investigated some sources of variability. This information was used in the construction of control charts. We have found evidence that classes with more students are associated with higher failure rates and lower mean. Moreover, when the course was later in the curriculum, the students had higher scores. The results showed that although they have been detected some special causes interfering in the process, it was possible to stabilize it and to monitor it.
Statistical analysis of disruptions in JET
International Nuclear Information System (INIS)
De Vries, P.C.; Johnson, M.F.; Segui, I.
2009-01-01
The disruption rate (the percentage of discharges that disrupt) in JET was found to drop steadily over the years. Recent campaigns (2005-2007) show a yearly averaged disruption rate of only 6% while from 1991 to 1995 this was often higher than 20%. Besides the disruption rate, the so-called disruptivity, or the likelihood of a disruption depending on the plasma parameters, has been determined. The disruptivity of plasmas was found to be significantly higher close to the three main operational boundaries for tokamaks; the low-q, high density and β-limit. The frequency at which JET operated close to the density-limit increased six fold over the last decade; however, only a small reduction in disruptivity was found. Similarly the disruptivity close to the low-q and β-limit was found to be unchanged. The most significant reduction in disruptivity was found far from the operational boundaries, leading to the conclusion that the improved disruption rate is due to a better technical capability of operating JET, instead of safer operations close to the physics limits. The statistics showed that a simple protection system was able to mitigate the forces of a large fraction of disruptions, although it has proved to be at present more difficult to ameliorate the heat flux.
The Statistical Analysis of Failure Time Data
Kalbfleisch, John D
2011-01-01
Contains additional discussion and examples on left truncation as well as material on more general censoring and truncation patterns.Introduces the martingale and counting process formulation swil lbe in a new chapter.Develops multivariate failure time data in a separate chapter and extends the material on Markov and semi Markov formulations.Presents new examples and applications of data analysis.
Avoiding Pitfalls in the Statistical Analysis of Heterogeneous Tumors
Directory of Open Access Journals (Sweden)
Judith-Anne W. Chapman
2009-01-01
Full Text Available Information about tumors is usually obtained from a single assessment of a tumor sample, performed at some point in the course of the development and progression of the tumor, with patient characteristics being surrogates for natural history context. Differences between cells within individual tumors (intratumor heterogeneity and between tumors of different patients (intertumor heterogeneity may mean that a small sample is not representative of the tumor as a whole, particularly for solid tumors which are the focus of this paper. This issue is of increasing importance as high-throughput technologies generate large multi-feature data sets in the areas of genomics, proteomics, and image analysis. Three potential pitfalls in statistical analysis are discussed (sampling, cut-points, and validation and suggestions are made about how to avoid these pitfalls.
CFAssay: statistical analysis of the colony formation assay
International Nuclear Information System (INIS)
Braselmann, Herbert; Michna, Agata; Heß, Julia; Unger, Kristian
2015-01-01
Colony formation assay is the gold standard to determine cell reproductive death after treatment with ionizing radiation, applied for different cell lines or in combination with other treatment modalities. Associated linear-quadratic cell survival curves can be calculated with different methods. For easy code exchange and methodological standardisation among collaborating laboratories a software package CFAssay for R (R Core Team, R: A Language and Environment for Statistical Computing, 2014) was established to perform thorough statistical analysis of linear-quadratic cell survival curves after treatment with ionizing radiation and of two-way designs of experiments with chemical treatments only. CFAssay offers maximum likelihood and related methods by default and the least squares or weighted least squares method can be optionally chosen. A test for comparision of cell survival curves and an ANOVA test for experimental two-way designs are provided. For the two presented examples estimated parameters do not differ much between maximum-likelihood and least squares. However the dispersion parameter of the quasi-likelihood method is much more sensitive for statistical variation in the data than the multiple R 2 coefficient of determination from the least squares method. The dispersion parameter for goodness of fit and different plot functions in CFAssay help to evaluate experimental data quality. As open source software interlaboratory code sharing between users is facilitated
The system for statistical analysis of logistic information
Directory of Open Access Journals (Sweden)
Khayrullin Rustam Zinnatullovich
2015-05-01
Full Text Available The current problem for managers in logistic and trading companies is the task of improving the operational business performance and developing the logistics support of sales. The development of logistics sales supposes development and implementation of a set of works for the development of the existing warehouse facilities, including both a detailed description of the work performed, and the timing of their implementation. Logistics engineering of warehouse complex includes such tasks as: determining the number and the types of technological zones, calculation of the required number of loading-unloading places, development of storage structures, development and pre-sales preparation zones, development of specifications of storage types, selection of loading-unloading equipment, detailed planning of warehouse logistics system, creation of architectural-planning decisions, selection of information-processing equipment, etc. The currently used ERP and WMS systems did not allow us to solve the full list of logistics engineering problems. In this regard, the development of specialized software products, taking into account the specifics of warehouse logistics, and subsequent integration of these software with ERP and WMS systems seems to be a current task. In this paper we suggest a system of statistical analysis of logistics information, designed to meet the challenges of logistics engineering and planning. The system is based on the methods of statistical data processing.The proposed specialized software is designed to improve the efficiency of the operating business and the development of logistics support of sales. The system is based on the methods of statistical data processing, the methods of assessment and prediction of logistics performance, the methods for the determination and calculation of the data required for registration, storage and processing of metal products, as well as the methods for planning the reconstruction and development
An analysis of UK wind farm statistics
International Nuclear Information System (INIS)
Milborrow, D.J.
1995-01-01
An analysis of key data for 22 completed wind projects shows 134 MW of plant cost Pound 152 million, giving an average cost of Pound 1136/kW. The energy generation potential of these windfarms is around 360 GWh, derived from sites with windspeeds between 6.2 and 8.8 m/s. Relationships between wind speed, energy production and cost were examined and it was found that costs increased with wind speed, due to the difficulties of access in hilly regions. It also appears that project costs fell with time and wind energy prices have fallen much faster than electricity prices. (Author)
EBprot: Statistical analysis of labeling-based quantitative proteomics data.
Koh, Hiromi W L; Swa, Hannah L F; Fermin, Damian; Ler, Siok Ghee; Gunaratne, Jayantha; Choi, Hyungwon
2015-08-01
Labeling-based proteomics is a powerful method for detection of differentially expressed proteins (DEPs). The current data analysis platform typically relies on protein-level ratios, which is obtained by summarizing peptide-level ratios for each protein. In shotgun proteomics, however, some proteins are quantified with more peptides than others, and this reproducibility information is not incorporated into the differential expression (DE) analysis. Here, we propose a novel probabilistic framework EBprot that directly models the peptide-protein hierarchy and rewards the proteins with reproducible evidence of DE over multiple peptides. To evaluate its performance with known DE states, we conducted a simulation study to show that the peptide-level analysis of EBprot provides better receiver-operating characteristic and more accurate estimation of the false discovery rates than the methods based on protein-level ratios. We also demonstrate superior classification performance of peptide-level EBprot analysis in a spike-in dataset. To illustrate the wide applicability of EBprot in different experimental designs, we applied EBprot to a dataset for lung cancer subtype analysis with biological replicates and another dataset for time course phosphoproteome analysis of EGF-stimulated HeLa cells with multiplexed labeling. Through these examples, we show that the peptide-level analysis of EBprot is a robust alternative to the existing statistical methods for the DE analysis of labeling-based quantitative datasets. The software suite is freely available on the Sourceforge website http://ebprot.sourceforge.net/. All MS data have been deposited in the ProteomeXchange with identifier PXD001426 (http://proteomecentral.proteomexchange.org/dataset/PXD001426/). © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
FADTTS: functional analysis of diffusion tensor tract statistics.
Zhu, Hongtu; Kong, Linglong; Li, Runze; Styner, Martin; Gerig, Guido; Lin, Weili; Gilmore, John H
2011-06-01
The aim of this paper is to present a functional analysis of a diffusion tensor tract statistics (FADTTS) pipeline for delineating the association between multiple diffusion properties along major white matter fiber bundles with a set of covariates of interest, such as age, diagnostic status and gender, and the structure of the variability of these white matter tract properties in various diffusion tensor imaging studies. The FADTTS integrates five statistical tools: (i) a multivariate varying coefficient model for allowing the varying coefficient functions in terms of arc length to characterize the varying associations between fiber bundle diffusion properties and a set of covariates, (ii) a weighted least squares estimation of the varying coefficient functions, (iii) a functional principal component analysis to delineate the structure of the variability in fiber bundle diffusion properties, (iv) a global test statistic to test hypotheses of interest, and (v) a simultaneous confidence band to quantify the uncertainty in the estimated coefficient functions. Simulated data are used to evaluate the finite sample performance of FADTTS. We apply FADTTS to investigate the development of white matter diffusivities along the splenium of the corpus callosum tract and the right internal capsule tract in a clinical study of neurodevelopment. FADTTS can be used to facilitate the understanding of normal brain development, the neural bases of neuropsychiatric disorders, and the joint effects of environmental and genetic factors on white matter fiber bundles. The advantages of FADTTS compared with the other existing approaches are that they are capable of modeling the structured inter-subject variability, testing the joint effects, and constructing their simultaneous confidence bands. However, FADTTS is not crucial for estimation and reduces to the functional analysis method for the single measure. Copyright © 2011 Elsevier Inc. All rights reserved.
A statistical analysis of UK financial networks
Chu, J.; Nadarajah, S.
2017-04-01
In recent years, with a growing interest in big or large datasets, there has been a rise in the application of large graphs and networks to financial big data. Much of this research has focused on the construction and analysis of the network structure of stock markets, based on the relationships between stock prices. Motivated by Boginski et al. (2005), who studied the characteristics of a network structure of the US stock market, we construct network graphs of the UK stock market using same method. We fit four distributions to the degree density of the vertices from these graphs, the Pareto I, Fréchet, lognormal, and generalised Pareto distributions, and assess the goodness of fit. Our results show that the degree density of the complements of the market graphs, constructed using a negative threshold value close to zero, can be fitted well with the Fréchet and lognormal distributions.
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.
Comparative analysis of positive and negative attitudes toward statistics
Ghulami, Hassan Rahnaward; Ab Hamid, Mohd Rashid; Zakaria, Roslinazairimah
2015-02-01
Many statistics lecturers and statistics education researchers are interested to know the perception of their students' attitudes toward statistics during the statistics course. In statistics course, positive attitude toward statistics is a vital because it will be encourage students to get interested in the statistics course and in order to master the core content of the subject matters under study. Although, students who have negative attitudes toward statistics they will feel depressed especially in the given group assignment, at risk for failure, are often highly emotional, and could not move forward. Therefore, this study investigates the students' attitude towards learning statistics. Six latent constructs have been the measurement of students' attitudes toward learning statistic such as affect, cognitive competence, value, difficulty, interest, and effort. The questionnaire was adopted and adapted from the reliable and validate instrument of Survey of Attitudes towards Statistics (SATS). This study is conducted among engineering undergraduate engineering students in the university Malaysia Pahang (UMP). The respondents consist of students who were taking the applied statistics course from different faculties. From the analysis, it is found that the questionnaire is acceptable and the relationships among the constructs has been proposed and investigated. In this case, students show full effort to master the statistics course, feel statistics course enjoyable, have confidence that they have intellectual capacity, and they have more positive attitudes then negative attitudes towards statistics learning. In conclusion in terms of affect, cognitive competence, value, interest and effort construct the positive attitude towards statistics was mostly exhibited. While negative attitudes mostly exhibited by difficulty construct.
CORSSA: The Community Online Resource for Statistical Seismicity Analysis
Michael, Andrew J.; Wiemer, Stefan
2010-01-01
Statistical seismology is the application of rigorous statistical methods to earthquake science with the goal of improving our knowledge of how the earth works. Within statistical seismology there is a strong emphasis on the analysis of seismicity data in order to improve our scientific understanding of earthquakes and to improve the evaluation and testing of earthquake forecasts, earthquake early warning, and seismic hazards assessments. Given the societal importance of these applications, statistical seismology must be done well. Unfortunately, a lack of educational resources and available software tools make it difficult for students and new practitioners to learn about this discipline. The goal of the Community Online Resource for Statistical Seismicity Analysis (CORSSA) is to promote excellence in statistical seismology by providing the knowledge and resources necessary to understand and implement the best practices, so that the reader can apply these methods to their own research. This introduction describes the motivation for and vision of CORRSA. It also describes its structure and contents.
Method for statistical data analysis of multivariate observations
Gnanadesikan, R
1997-01-01
A practical guide for multivariate statistical techniques-- now updated and revised In recent years, innovations in computer technology and statistical methodologies have dramatically altered the landscape of multivariate data analysis. This new edition of Methods for Statistical Data Analysis of Multivariate Observations explores current multivariate concepts and techniques while retaining the same practical focus of its predecessor. It integrates methods and data-based interpretations relevant to multivariate analysis in a way that addresses real-world problems arising in many areas of inte
Online Statistical Modeling (Regression Analysis) for Independent Responses
Made Tirta, I.; Anggraeni, Dian; Pandutama, Martinus
2017-06-01
Regression analysis (statistical analmodelling) are among statistical methods which are frequently needed in analyzing quantitative data, especially to model relationship between response and explanatory variables. Nowadays, statistical models have been developed into various directions to model various type and complex relationship of data. Rich varieties of advanced and recent statistical modelling are mostly available on open source software (one of them is R). However, these advanced statistical modelling, are not very friendly to novice R users, since they are based on programming script or command line interface. Our research aims to developed web interface (based on R and shiny), so that most recent and advanced statistical modelling are readily available, accessible and applicable on web. We have previously made interface in the form of e-tutorial for several modern and advanced statistical modelling on R especially for independent responses (including linear models/LM, generalized linier models/GLM, generalized additive model/GAM and generalized additive model for location scale and shape/GAMLSS). In this research we unified them in the form of data analysis, including model using Computer Intensive Statistics (Bootstrap and Markov Chain Monte Carlo/ MCMC). All are readily accessible on our online Virtual Statistics Laboratory. The web (interface) make the statistical modeling becomes easier to apply and easier to compare them in order to find the most appropriate model for the data.
Statistical Analysis and Modelling of Olkiluoto Structures
International Nuclear Information System (INIS)
Hellae, P.; Vaittinen, T.; Saksa, P.; Nummela, J.
2004-11-01
Posiva Oy is carrying out investigations for the disposal of the spent nuclear fuel at the Olkiluoto site in SW Finland. The investigations have focused on the central part of the island. The layout design of the entire repository requires characterization of notably larger areas and must rely at least at the current stage on borehole information from a rather sparse network and on the geophysical soundings providing information outside and between the holes. In this work, the structural data according to the current version of the Olkiluoto bedrock model is analyzed. The bedrock model relies much on the borehole data although results of the seismic surveys and, for example, pumping tests are used in determining the orientation and continuation of the structures. Especially in the analysis, questions related to the frequency of structures and size of the structures are discussed. The structures observed in the boreholes are mainly dipping gently to the southeast. About 9 % of the sample length belongs to structures. The proportion is higher in the upper parts of the rock. The number of fracture and crushed zones seems not to depend greatly on the depth, whereas the hydraulic features concentrate on the depth range above -100 m. Below level -300 m, the hydraulic conductivity occurs in connection of fractured zones. Especially the hydraulic features, but also fracture and crushed zones often occur in groups. The frequency of the structure (area of structures per total volume) is estimated to be of the order of 1/100m. The size of the local structures was estimated by calculating the intersection of the zone to the nearest borehole where the zone has not been detected. Stochastic models using the Fracman software by Golder Associates were generated based on the bedrock model data complemented with the magnetic ground survey data. The seismic surveys (from boreholes KR5, KR13, KR14, and KR19) were used as alternative input data. The generated models were tested by
Explorations in Statistics: The Analysis of Ratios and Normalized Data
Curran-Everett, Douglas
2013-01-01
Learning about statistics is a lot like learning about science: the learning is more meaningful if you can actively explore. This ninth installment of "Explorations in Statistics" explores the analysis of ratios and normalized--or standardized--data. As researchers, we compute a ratio--a numerator divided by a denominator--to compute a…
Analysis of thrips distribution: application of spatial statistics and Kriging
John Aleong; Bruce L. Parker; Margaret Skinner; Diantha Howard
1991-01-01
Kriging is a statistical technique that provides predictions for spatially and temporally correlated data. Observations of thrips distribution and density in Vermont soils are made in both space and time. Traditional statistical analysis of such data assumes that the counts taken over space and time are independent, which is not necessarily true. Therefore, to analyze...
Performing data analysis using IBM SPSS
Meyers, Lawrence S; Guarino, A J
2013-01-01
This book is designed to be a user's guide for students and other interested readers to perform statistical data analysis with IBM SPSS, which is a major statistical software package used extensively in academic, government, and business settings. This book addresses the needs, level of sophistication, and interest in introductory statistical methodology on the part of undergraduate and graduate students in social and behavioral science, business, health-related, and education programs. Each chapter covers a particular statistical procedure and has the following format: an example pr
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
Statistical analysis of the count and profitability of air conditioners.
Rady, El Houssainy A; Mohamed, Salah M; Abd Elmegaly, Alaa A
2018-08-01
This article presents the statistical analysis of the number and profitability of air conditioners in an Egyptian company. Checking the same distribution for each categorical variable has been made using Kruskal-Wallis test.
Instrumental Neutron Activation Analysis and Multivariate Statistics for Pottery Provenance
Glascock, M. D.; Neff, H.; Vaughn, K. J.
2004-06-01
The application of instrumental neutron activation analysis and multivariate statistics to archaeological studies of ceramics and clays is described. A small pottery data set from the Nasca culture in southern Peru is presented for illustration.
Instrumental Neutron Activation Analysis and Multivariate Statistics for Pottery Provenance
International Nuclear Information System (INIS)
Glascock, M. D.; Neff, H.; Vaughn, K. J.
2004-01-01
The application of instrumental neutron activation analysis and multivariate statistics to archaeological studies of ceramics and clays is described. A small pottery data set from the Nasca culture in southern Peru is presented for illustration.
Application of Ontology Technology in Health Statistic Data Analysis.
Guo, Minjiang; Hu, Hongpu; Lei, Xingyun
2017-01-01
Research Purpose: establish health management ontology for analysis of health statistic data. Proposed Methods: this paper established health management ontology based on the analysis of the concepts in China Health Statistics Yearbook, and used protégé to define the syntactic and semantic structure of health statistical data. six classes of top-level ontology concepts and their subclasses had been extracted and the object properties and data properties were defined to establish the construction of these classes. By ontology instantiation, we can integrate multi-source heterogeneous data and enable administrators to have an overall understanding and analysis of the health statistic data. ontology technology provides a comprehensive and unified information integration structure of the health management domain and lays a foundation for the efficient analysis of multi-source and heterogeneous health system management data and enhancement of the management efficiency.
Instrumental Neutron Activation Analysis and Multivariate Statistics for Pottery Provenance
Energy Technology Data Exchange (ETDEWEB)
Glascock, M. D.; Neff, H. [University of Missouri, Research Reactor Center (United States); Vaughn, K. J. [Pacific Lutheran University, Department of Anthropology (United States)
2004-06-15
The application of instrumental neutron activation analysis and multivariate statistics to archaeological studies of ceramics and clays is described. A small pottery data set from the Nasca culture in southern Peru is presented for illustration.
Evaluation of the performance of Moses statistical engine adapted to ...
African Journals Online (AJOL)
... of Moses statistical engine adapted to English-Arabic language combination. ... of Artificial Intelligence (AI) dedicated to Natural Language Processing (NLP). ... and focuses on SMT, then introducing the features of the open source Moses ...
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
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
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
Propensity Score Analysis: An Alternative Statistical Approach for HRD Researchers
Keiffer, Greggory L.; Lane, Forrest C.
2016-01-01
Purpose: This paper aims to introduce matching in propensity score analysis (PSA) as an alternative statistical approach for researchers looking to make causal inferences using intact groups. Design/methodology/approach: An illustrative example demonstrated the varying results of analysis of variance, analysis of covariance and PSA on a heuristic…
Advanced data analysis in neuroscience integrating statistical and computational models
Durstewitz, Daniel
2017-01-01
This book is intended for use in advanced graduate courses in statistics / machine learning, as well as for all experimental neuroscientists seeking to understand statistical methods at a deeper level, and theoretical neuroscientists with a limited background in statistics. It reviews almost all areas of applied statistics, from basic statistical estimation and test theory, linear and nonlinear approaches for regression and classification, to model selection and methods for dimensionality reduction, density estimation and unsupervised clustering. Its focus, however, is linear and nonlinear time series analysis from a dynamical systems perspective, based on which it aims to convey an understanding also of the dynamical mechanisms that could have generated observed time series. Further, it integrates computational modeling of behavioral and neural dynamics with statistical estimation and hypothesis testing. This way computational models in neuroscience are not only explanat ory frameworks, but become powerfu...
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.
Short-run and Current Analysis Model in Statistics
Directory of Open Access Journals (Sweden)
Constantin Anghelache
2006-01-01
Full Text Available Using the short-run statistic indicators is a compulsory requirement implied in the current analysis. Therefore, there is a system of EUROSTAT indicators on short run which has been set up in this respect, being recommended for utilization by the member-countries. On the basis of these indicators, there are regular, usually monthly, analysis being achieved in respect of: the production dynamic determination; the evaluation of the short-run investment volume; the development of the turnover; the wage evolution: the employment; the price indexes and the consumer price index (inflation; the volume of exports and imports and the extent to which the imports are covered by the exports and the sold of trade balance. The EUROSTAT system of indicators of conjuncture is conceived as an open system, so that it can be, at any moment extended or restricted, allowing indicators to be amended or even removed, depending on the domestic users requirements as well as on the specific requirements of the harmonization and integration. For the short-run analysis, there is also the World Bank system of indicators of conjuncture, which is utilized, relying on the data sources offered by the World Bank, The World Institute for Resources or other international organizations statistics. The system comprises indicators of the social and economic development and focuses on the indicators for the following three fields: human resources, environment and economic performances. At the end of the paper, there is a case study on the situation of Romania, for which we used all these indicators.
Short-run and Current Analysis Model in Statistics
Directory of Open Access Journals (Sweden)
Constantin Mitrut
2006-03-01
Full Text Available Using the short-run statistic indicators is a compulsory requirement implied in the current analysis. Therefore, there is a system of EUROSTAT indicators on short run which has been set up in this respect, being recommended for utilization by the member-countries. On the basis of these indicators, there are regular, usually monthly, analysis being achieved in respect of: the production dynamic determination; the evaluation of the short-run investment volume; the development of the turnover; the wage evolution: the employment; the price indexes and the consumer price index (inflation; the volume of exports and imports and the extent to which the imports are covered by the exports and the sold of trade balance. The EUROSTAT system of indicators of conjuncture is conceived as an open system, so that it can be, at any moment extended or restricted, allowing indicators to be amended or even removed, depending on the domestic users requirements as well as on the specific requirements of the harmonization and integration. For the short-run analysis, there is also the World Bank system of indicators of conjuncture, which is utilized, relying on the data sources offered by the World Bank, The World Institute for Resources or other international organizations statistics. The system comprises indicators of the social and economic development and focuses on the indicators for the following three fields: human resources, environment and economic performances. At the end of the paper, there is a case study on the situation of Romania, for which we used all these indicators.
Analysis of filament statistics in fast camera data on MAST
Farley, Tom; Militello, Fulvio; Walkden, Nick; Harrison, James; Silburn, Scott; Bradley, James
2017-10-01
Coherent filamentary structures have been shown to play a dominant role in turbulent cross-field particle transport [D'Ippolito 2011]. An improved understanding of filaments is vital in order to control scrape off layer (SOL) density profiles and thus control first wall erosion, impurity flushing and coupling of radio frequency heating in future devices. The Elzar code [T. Farley, 2017 in prep.] is applied to MAST data. The code uses information about the magnetic equilibrium to calculate the intensity of light emission along field lines as seen in the camera images, as a function of the field lines' radial and toroidal locations at the mid-plane. In this way a `pseudo-inversion' of the intensity profiles in the camera images is achieved from which filaments can be identified and measured. In this work, a statistical analysis of the intensity fluctuations along field lines in the camera field of view is performed using techniques similar to those typically applied in standard Langmuir probe analyses. These filament statistics are interpreted in terms of the theoretical ergodic framework presented by F. Militello & J.T. Omotani, 2016, in order to better understand how time averaged filament dynamics produce the more familiar SOL density profiles. This work has received funding from the RCUK Energy programme (Grant Number EP/P012450/1), from Euratom (Grant Agreement No. 633053) and from the EUROfusion consortium.
A statistically self-consistent type Ia supernova data analysis
International Nuclear Information System (INIS)
Lago, B.L.; Calvao, M.O.; Joras, S.E.; Reis, R.R.R.; Waga, I.; Giostri, R.
2011-01-01
Full text: The type Ia supernovae are one of the main cosmological probes nowadays and are used as standardized candles in distance measurements. The standardization processes, among which SALT2 and MLCS2k2 are the most used ones, are based on empirical relations and leave room for a residual dispersion in the light curves of the supernovae. This dispersion is introduced in the chi squared used to fit the parameters of the model in the expression for the variance of the data, as an attempt to quantify our ignorance in modeling the supernovae properly. The procedure used to assign a value to this dispersion is statistically inconsistent and excludes the possibility of comparing different cosmological models. In addition, the SALT2 light curve fitter introduces parameters on the model for the variance that are also used in the model for the data. In the chi squared statistics context the minimization of such a quantity yields, in the best case scenario, a bias. An iterative method has been developed in order to perform the minimization of this chi squared but it is not well grounded, although it is used by several groups. We propose an analysis of the type Ia supernovae data that is based on the likelihood itself and makes it possible to address both inconsistencies mentioned above in a straightforward way. (author)
Statistical analysis and Kalman filtering applied to nuclear materials accountancy
International Nuclear Information System (INIS)
Annibal, P.S.
1990-08-01
Much theoretical research has been carried out on the development of statistical methods for nuclear material accountancy. In practice, physical, financial and time constraints mean that the techniques must be adapted to give an optimal performance in plant conditions. This thesis aims to bridge the gap between theory and practice, to show the benefits to be gained from a knowledge of the facility operation. Four different aspects are considered; firstly, the use of redundant measurements to reduce the error on the estimate of the mass of heavy metal in an 'accountancy tank' is investigated. Secondly, an analysis of the calibration data for the same tank is presented, establishing bounds for the error and suggesting a means of reducing them. Thirdly, a plant-specific method of producing an optimal statistic from the input, output and inventory data, to help decide between 'material loss' and 'no loss' hypotheses, is developed and compared with existing general techniques. Finally, an application of the Kalman Filter to materials accountancy is developed, to demonstrate the advantages of state-estimation techniques. The results of the analyses and comparisons illustrate the importance of taking into account a complete and accurate knowledge of the plant operation, measurement system, and calibration methods, to derive meaningful results from statistical tests on materials accountancy data, and to give a better understanding of critical random and systematic error sources. The analyses were carried out on the head-end of the Fast Reactor Reprocessing Plant, where fuel from the prototype fast reactor is cut up and dissolved. However, the techniques described are general in their application. (author)
Using robust statistics to improve neutron activation analysis results
International Nuclear Information System (INIS)
Zahn, Guilherme S.; Genezini, Frederico A.; Ticianelli, Regina B.; Figueiredo, Ana Maria G.
2011-01-01
Neutron activation analysis (NAA) is an analytical technique where an unknown sample is submitted to a neutron flux in a nuclear reactor, and its elemental composition is calculated by measuring the induced activity produced. By using the relative NAA method, one or more well-characterized samples (usually certified reference materials - CRMs) are irradiated together with the unknown ones, and the concentration of each element is then calculated by comparing the areas of the gamma ray peaks related to that element. When two or more CRMs are used as reference, the concentration of each element can be determined by several different ways, either using more than one gamma ray peak for that element (when available), or using the results obtained in the comparison with each CRM. Therefore, determining the best estimate for the concentration of each element in the sample can be a delicate issue. In this work, samples from three CRMs were irradiated together and the elemental concentration in one of them was calculated using the other two as reference. Two sets of peaks were analyzed for each element: a smaller set containing only the literature-recommended gamma-ray peaks and a larger one containing all peaks related to that element that could be quantified in the gamma-ray spectra; the most recommended transition was also used as a benchmark. The resulting data for each element was then reduced using up to five different statistical approaches: the usual (and not robust) unweighted and weighted means, together with three robust means: the Limitation of Relative Statistical Weight, Normalized Residuals and Rajeval. The resulting concentration values were then compared to the certified value for each element, allowing for discussion on both the performance of each statistical tool and on the best choice of peaks for each element. (author)
Performance analysis in saber.
Aquili, Andrea; Tancredi, Virginia; Triossi, Tamara; De Sanctis, Desiree; Padua, Elvira; DʼArcangelo, Giovanna; Melchiorri, Giovanni
2013-03-01
Fencing is a sport practiced by both men and women, which uses 3 weapons: foil, épée, and saber. In general, there are few scientific studies available in international literature; they are limited to the performance analysis of fencing bouts, yet there is nothing about saber. There are 2 kinds of competitions in the World Cup for both men and women: the "FIE GP" and "A." The aim of this study was to carry out a saber performance analysis to gain useful indicators for the definition of a performance model. In addition, it is expected to verify if it could be influenced by the type of competition and if there are differences between men and women. Sixty bouts: 33 FIE GP and 27 "A" competitions (35 men's and 25 women's saber bouts) were analyzed. The results indicated that most actions are offensive (55% for men and 49% for women); the central area of the piste is mostly used (72% for men and 67% for women); the effective fighting time is 13.6% for men and 17.1% for women, and the ratio between the action and break times is 1:6.5 for men and 1:5.1 for women. A lunge is carried out every 23.9 seconds by men and every 20 seconds by women, and a direction change is carried out every 65.3 seconds by men and every 59.7 seconds by women. The data confirm the differences between the saber and the other 2 weapons. There is no significant difference between the data of the 2 different kinds of competitions.
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
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
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
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.
Numeric computation and statistical data analysis on the Java platform
Chekanov, Sergei V
2016-01-01
Numerical computation, knowledge discovery and statistical data analysis integrated with powerful 2D and 3D graphics for visualization are the key topics of this book. The Python code examples powered by the Java platform can easily be transformed to other programming languages, such as Java, Groovy, Ruby and BeanShell. This book equips the reader with a computational platform which, unlike other statistical programs, is not limited by a single programming language. The author focuses on practical programming aspects and covers a broad range of topics, from basic introduction to the Python language on the Java platform (Jython), to descriptive statistics, symbolic calculations, neural networks, non-linear regression analysis and many other data-mining topics. He discusses how to find regularities in real-world data, how to classify data, and how to process data for knowledge discoveries. The code snippets are so short that they easily fit into single pages. Numeric Computation and Statistical Data Analysis ...
Analysis of room transfer function and reverberant signal statistics
DEFF Research Database (Denmark)
Georganti, Eleftheria; Mourjopoulos, John; Jacobsen, Finn
2008-01-01
For some time now, statistical analysis has been a valuable tool in analyzing room transfer functions (RTFs). This work examines existing statistical time-frequency models and techniques for RTF analysis (e.g., Schroeder's stochastic model and the standard deviation over frequency bands for the RTF...... magnitude and phase). RTF fractional octave smoothing, as with 1-slash 3 octave analysis, may lead to RTF simplifications that can be useful for several audio applications, like room compensation, room modeling, auralisation purposes. The aim of this work is to identify the relationship of optimal response...... and the corresponding ratio of the direct and reverberant signal. In addition, this work examines the statistical quantities for speech and audio signals prior to their reproduction within rooms and when recorded in rooms. Histograms and other statistical distributions are used to compare RTF minima of typical...
Measuring the Success of an Academic Development Programme: A Statistical Analysis
Smith, L. C.
2009-01-01
This study uses statistical analysis to estimate the impact of first-year academic development courses in microeconomics, statistics, accountancy, and information systems, offered by the University of Cape Town's Commerce Academic Development Programme, on students' graduation performance relative to that achieved by mainstream students. The data…
Simulation Experiments in Practice: Statistical Design and Regression Analysis
Kleijnen, J.P.C.
2007-01-01
In practice, simulation analysts often change only one factor at a time, and use graphical analysis of the resulting Input/Output (I/O) data. The goal of this article is to change these traditional, naïve methods of design and analysis, because statistical theory proves that more information is obtained when applying Design Of Experiments (DOE) and linear regression analysis. Unfortunately, classic DOE and regression analysis assume a single simulation response that is normally and independen...
Paechter, Manuela; Macher, Daniel; Martskvishvili, Khatuna; Wimmer, Sigrid; Papousek, Ilona
2017-01-01
In many social science majors, e.g., psychology, students report high levels of statistics anxiety. However, these majors are often chosen by students who are less prone to mathematics and who might have experienced difficulties and unpleasant feelings in their mathematics courses at school. The present study investigates whether statistics anxiety is a genuine form of anxiety that impairs students' achievements or whether learners mainly transfer previous experiences in mathematics and their anxiety in mathematics to statistics. The relationship between mathematics anxiety and statistics anxiety, their relationship to learning behaviors and to performance in a statistics examination were investigated in a sample of 225 undergraduate psychology students (164 women, 61 men). Data were recorded at three points in time: At the beginning of term students' mathematics anxiety, general proneness to anxiety, school grades, and demographic data were assessed; 2 weeks before the end of term, they completed questionnaires on statistics anxiety and their learning behaviors. At the end of term, examination scores were recorded. Mathematics anxiety and statistics anxiety correlated highly but the comparison of different structural equation models showed that they had genuine and even antagonistic contributions to learning behaviors and performance in the examination. Surprisingly, mathematics anxiety was positively related to performance. It might be that students realized over the course of their first term that knowledge and skills in higher secondary education mathematics are not sufficient to be successful in statistics. Part of mathematics anxiety may then have strengthened positive extrinsic effort motivation by the intention to avoid failure and may have led to higher effort for the exam preparation. However, via statistics anxiety mathematics anxiety also had a negative contribution to performance. Statistics anxiety led to higher procrastination in the structural
Paechter, Manuela; Macher, Daniel; Martskvishvili, Khatuna; Wimmer, Sigrid; Papousek, Ilona
2017-01-01
In many social science majors, e.g., psychology, students report high levels of statistics anxiety. However, these majors are often chosen by students who are less prone to mathematics and who might have experienced difficulties and unpleasant feelings in their mathematics courses at school. The present study investigates whether statistics anxiety is a genuine form of anxiety that impairs students' achievements or whether learners mainly transfer previous experiences in mathematics and their anxiety in mathematics to statistics. The relationship between mathematics anxiety and statistics anxiety, their relationship to learning behaviors and to performance in a statistics examination were investigated in a sample of 225 undergraduate psychology students (164 women, 61 men). Data were recorded at three points in time: At the beginning of term students' mathematics anxiety, general proneness to anxiety, school grades, and demographic data were assessed; 2 weeks before the end of term, they completed questionnaires on statistics anxiety and their learning behaviors. At the end of term, examination scores were recorded. Mathematics anxiety and statistics anxiety correlated highly but the comparison of different structural equation models showed that they had genuine and even antagonistic contributions to learning behaviors and performance in the examination. Surprisingly, mathematics anxiety was positively related to performance. It might be that students realized over the course of their first term that knowledge and skills in higher secondary education mathematics are not sufficient to be successful in statistics. Part of mathematics anxiety may then have strengthened positive extrinsic effort motivation by the intention to avoid failure and may have led to higher effort for the exam preparation. However, via statistics anxiety mathematics anxiety also had a negative contribution to performance. Statistics anxiety led to higher procrastination in the structural
Directory of Open Access Journals (Sweden)
Manuela Paechter
2017-07-01
Full Text Available In many social science majors, e.g., psychology, students report high levels of statistics anxiety. However, these majors are often chosen by students who are less prone to mathematics and who might have experienced difficulties and unpleasant feelings in their mathematics courses at school. The present study investigates whether statistics anxiety is a genuine form of anxiety that impairs students' achievements or whether learners mainly transfer previous experiences in mathematics and their anxiety in mathematics to statistics. The relationship between mathematics anxiety and statistics anxiety, their relationship to learning behaviors and to performance in a statistics examination were investigated in a sample of 225 undergraduate psychology students (164 women, 61 men. Data were recorded at three points in time: At the beginning of term students' mathematics anxiety, general proneness to anxiety, school grades, and demographic data were assessed; 2 weeks before the end of term, they completed questionnaires on statistics anxiety and their learning behaviors. At the end of term, examination scores were recorded. Mathematics anxiety and statistics anxiety correlated highly but the comparison of different structural equation models showed that they had genuine and even antagonistic contributions to learning behaviors and performance in the examination. Surprisingly, mathematics anxiety was positively related to performance. It might be that students realized over the course of their first term that knowledge and skills in higher secondary education mathematics are not sufficient to be successful in statistics. Part of mathematics anxiety may then have strengthened positive extrinsic effort motivation by the intention to avoid failure and may have led to higher effort for the exam preparation. However, via statistics anxiety mathematics anxiety also had a negative contribution to performance. Statistics anxiety led to higher procrastination in
Statistical analysis of the uncertainty related to flood hazard appraisal
Notaro, Vincenza; Freni, Gabriele
2015-12-01
The estimation of flood hazard frequency statistics for an urban catchment is of great interest in practice. It provides the evaluation of potential flood risk and related damage and supports decision making for flood risk management. Flood risk is usually defined as function of the probability, that a system deficiency can cause flooding (hazard), and the expected damage, due to the flooding magnitude (damage), taking into account both the exposure and the vulnerability of the goods at risk. The expected flood damage can be evaluated by an a priori estimation of potential damage caused by flooding or by interpolating real damage data. With regard to flood hazard appraisal several procedures propose to identify some hazard indicator (HI) such as flood depth or the combination of flood depth and velocity and to assess the flood hazard corresponding to the analyzed area comparing the HI variables with user-defined threshold values or curves (penalty curves or matrixes). However, flooding data are usually unavailable or piecemeal allowing for carrying out a reliable flood hazard analysis, therefore hazard analysis is often performed by means of mathematical simulations aimed at evaluating water levels and flow velocities over catchment surface. As results a great part of the uncertainties intrinsic to flood risk appraisal can be related to the hazard evaluation due to the uncertainty inherent to modeling results and to the subjectivity of the user defined hazard thresholds applied to link flood depth to a hazard level. In the present work, a statistical methodology was proposed for evaluating and reducing the uncertainties connected with hazard level estimation. The methodology has been applied to a real urban watershed as case study.
Classification of Malaysia aromatic rice using multivariate statistical analysis
International Nuclear Information System (INIS)
Abdullah, A. H.; Adom, A. H.; Shakaff, A. Y. Md; Masnan, M. J.; Zakaria, A.; Rahim, N. A.; Omar, O.
2015-01-01
Aromatic rice (Oryza sativa L.) is considered as the best quality premium rice. The varieties are preferred by consumers because of its preference criteria such as shape, colour, distinctive aroma and flavour. The price of aromatic rice is higher than ordinary rice due to its special needed growth condition for instance specific climate and soil. Presently, the aromatic rice quality is identified by using its key elements and isotopic variables. The rice can also be classified via Gas Chromatography Mass Spectrometry (GC-MS) or human sensory panels. However, the uses of human sensory panels have significant drawbacks such as lengthy training time, and prone to fatigue as the number of sample increased and inconsistent. The GC–MS analysis techniques on the other hand, require detailed procedures, lengthy analysis and quite costly. This paper presents the application of in-house developed Electronic Nose (e-nose) to classify new aromatic rice varieties. The e-nose is used to classify the variety of aromatic rice based on the samples odour. The samples were taken from the variety of rice. The instrument utilizes multivariate statistical data analysis, including Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA) and K-Nearest Neighbours (KNN) to classify the unknown rice samples. The Leave-One-Out (LOO) validation approach is applied to evaluate the ability of KNN to perform recognition and classification of the unspecified samples. The visual observation of the PCA and LDA plots of the rice proves that the instrument was able to separate the samples into different clusters accordingly. The results of LDA and KNN with low misclassification error support the above findings and we may conclude that the e-nose is successfully applied to the classification of the aromatic rice varieties
Classification of Malaysia aromatic rice using multivariate statistical analysis
Energy Technology Data Exchange (ETDEWEB)
Abdullah, A. H.; Adom, A. H.; Shakaff, A. Y. Md; Masnan, M. J.; Zakaria, A.; Rahim, N. A. [School of Mechatronic Engineering, Universiti Malaysia Perlis, Kampus Pauh Putra, 02600 Arau, Perlis (Malaysia); Omar, O. [Malaysian Agriculture Research and Development Institute (MARDI), Persiaran MARDI-UPM, 43400 Serdang, Selangor (Malaysia)
2015-05-15
Aromatic rice (Oryza sativa L.) is considered as the best quality premium rice. The varieties are preferred by consumers because of its preference criteria such as shape, colour, distinctive aroma and flavour. The price of aromatic rice is higher than ordinary rice due to its special needed growth condition for instance specific climate and soil. Presently, the aromatic rice quality is identified by using its key elements and isotopic variables. The rice can also be classified via Gas Chromatography Mass Spectrometry (GC-MS) or human sensory panels. However, the uses of human sensory panels have significant drawbacks such as lengthy training time, and prone to fatigue as the number of sample increased and inconsistent. The GC–MS analysis techniques on the other hand, require detailed procedures, lengthy analysis and quite costly. This paper presents the application of in-house developed Electronic Nose (e-nose) to classify new aromatic rice varieties. The e-nose is used to classify the variety of aromatic rice based on the samples odour. The samples were taken from the variety of rice. The instrument utilizes multivariate statistical data analysis, including Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA) and K-Nearest Neighbours (KNN) to classify the unknown rice samples. The Leave-One-Out (LOO) validation approach is applied to evaluate the ability of KNN to perform recognition and classification of the unspecified samples. The visual observation of the PCA and LDA plots of the rice proves that the instrument was able to separate the samples into different clusters accordingly. The results of LDA and KNN with low misclassification error support the above findings and we may conclude that the e-nose is successfully applied to the classification of the aromatic rice varieties.
Classification of Malaysia aromatic rice using multivariate statistical analysis
Abdullah, A. H.; Adom, A. H.; Shakaff, A. Y. Md; Masnan, M. J.; Zakaria, A.; Rahim, N. A.; Omar, O.
2015-05-01
Aromatic rice (Oryza sativa L.) is considered as the best quality premium rice. The varieties are preferred by consumers because of its preference criteria such as shape, colour, distinctive aroma and flavour. The price of aromatic rice is higher than ordinary rice due to its special needed growth condition for instance specific climate and soil. Presently, the aromatic rice quality is identified by using its key elements and isotopic variables. The rice can also be classified via Gas Chromatography Mass Spectrometry (GC-MS) or human sensory panels. However, the uses of human sensory panels have significant drawbacks such as lengthy training time, and prone to fatigue as the number of sample increased and inconsistent. The GC-MS analysis techniques on the other hand, require detailed procedures, lengthy analysis and quite costly. This paper presents the application of in-house developed Electronic Nose (e-nose) to classify new aromatic rice varieties. The e-nose is used to classify the variety of aromatic rice based on the samples odour. The samples were taken from the variety of rice. The instrument utilizes multivariate statistical data analysis, including Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA) and K-Nearest Neighbours (KNN) to classify the unknown rice samples. The Leave-One-Out (LOO) validation approach is applied to evaluate the ability of KNN to perform recognition and classification of the unspecified samples. The visual observation of the PCA and LDA plots of the rice proves that the instrument was able to separate the samples into different clusters accordingly. The results of LDA and KNN with low misclassification error support the above findings and we may conclude that the e-nose is successfully applied to the classification of the aromatic rice varieties.
Statistical analysis of planktic foraminifera of the surface Continental ...
African Journals Online (AJOL)
Planktic foraminiferal assemblage recorded from selected samples obtained from shallow continental shelf sediments off southwestern Nigeria were subjected to statistical analysis. The Principal Component Analysis (PCA) was used to determine variants of planktic parameters. Values obtained for these parameters were ...
Simulation Experiments in Practice : Statistical Design and Regression Analysis
Kleijnen, J.P.C.
2007-01-01
In practice, simulation analysts often change only one factor at a time, and use graphical analysis of the resulting Input/Output (I/O) data. Statistical theory proves that more information is obtained when applying Design Of Experiments (DOE) and linear regression analysis. Unfortunately, classic
Simulation Experiments in Practice : Statistical Design and Regression Analysis
Kleijnen, J.P.C.
2007-01-01
In practice, simulation analysts often change only one factor at a time, and use graphical analysis of the resulting Input/Output (I/O) data. The goal of this article is to change these traditional, naïve methods of design and analysis, because statistical theory proves that more information is
PRECISE - pregabalin in addition to usual care: Statistical analysis plan
S. Mathieson (Stephanie); L. Billot (Laurent); C. Maher (Chris); A.J. McLachlan (Andrew J.); J. Latimer (Jane); B.W. Koes (Bart); M.J. Hancock (Mark J.); I. Harris (Ian); R.O. Day (Richard O.); J. Pik (Justin); S. Jan (Stephen); C.-W.C. Lin (Chung-Wei Christine)
2016-01-01
textabstractBackground: Sciatica is a severe, disabling condition that lacks high quality evidence for effective treatment strategies. This a priori statistical analysis plan describes the methodology of analysis for the PRECISE study. Methods/design: PRECISE is a prospectively registered, double
Statistical analysis applied to safety culture self-assessment
International Nuclear Information System (INIS)
Macedo Soares, P.P.
2002-01-01
Interviews and opinion surveys are instruments used to assess the safety culture in an organization as part of the Safety Culture Enhancement Programme. Specific statistical tools are used to analyse the survey results. This paper presents an example of an opinion survey with the corresponding application of the statistical analysis and the conclusions obtained. Survey validation, Frequency statistics, Kolmogorov-Smirnov non-parametric test, Student (T-test) and ANOVA means comparison tests and LSD post-hoc multiple comparison test, are discussed. (author)
Longitudinal data analysis a handbook of modern statistical methods
Fitzmaurice, Garrett; Verbeke, Geert; Molenberghs, Geert
2008-01-01
Although many books currently available describe statistical models and methods for analyzing longitudinal data, they do not highlight connections between various research threads in the statistical literature. Responding to this void, Longitudinal Data Analysis provides a clear, comprehensive, and unified overview of state-of-the-art theory and applications. It also focuses on the assorted challenges that arise in analyzing longitudinal data. After discussing historical aspects, leading researchers explore four broad themes: parametric modeling, nonparametric and semiparametric methods, joint
Highly Robust Statistical Methods in Medical Image Analysis
Czech Academy of Sciences Publication Activity Database
Kalina, Jan
2012-01-01
Roč. 32, č. 2 (2012), s. 3-16 ISSN 0208-5216 R&D Projects: GA MŠk(CZ) 1M06014 Institutional research plan: CEZ:AV0Z10300504 Keywords : robust statistics * classification * faces * robust image analysis * forensic science Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 0.208, year: 2012 http://www.ibib.waw.pl/bbe/bbefulltext/BBE_32_2_003_FT.pdf
Network similarity and statistical analysis of earthquake seismic data
Deyasi, Krishanu; Chakraborty, Abhijit; Banerjee, Anirban
2016-01-01
We study the structural similarity of earthquake networks constructed from seismic catalogs of different geographical regions. A hierarchical clustering of underlying undirected earthquake networks is shown using Jensen-Shannon divergence in graph spectra. The directed nature of links indicates that each earthquake network is strongly connected, which motivates us to study the directed version statistically. Our statistical analysis of each earthquake region identifies the hub regions. We cal...
Performance Monitoring System: Summary of Lock Statistics. Revision 1.
1985-12-01
2751 84 4057 4141 526 798 18 1342 5727 19 5523 3996 4587 8583 1056 1630 35 2721 6536LOCK A DAMI 2 AUXILIARY I Ins NO DATA RECORDD FOR THIS LOCK- " LOCK I...TOTAL (KTOMS) ’ - (AVt OPNP ETC) ’’ ,q [ " ARKANSAS RIVER "" FORRELL LOCK IP 7A/3TRC 9/N83 UPBOUID STATISTICS ISO 53 42 M6 553 356 909 221 41 21 M8
FTree query construction for virtual screening: a statistical analysis.
Gerlach, Christof; Broughton, Howard; Zaliani, Andrea
2008-02-01
FTrees (FT) is a known chemoinformatic tool able to condense molecular descriptions into a graph object and to search for actives in large databases using graph similarity. The query graph is classically derived from a known active molecule, or a set of actives, for which a similar compound has to be found. Recently, FT similarity has been extended to fragment space, widening its capabilities. If a user were able to build a knowledge-based FT query from information other than a known active structure, the similarity search could be combined with other, normally separate, fields like de-novo design or pharmacophore searches. With this aim in mind, we performed a comprehensive analysis of several databases in terms of FT description and provide a basic statistical analysis of the FT spaces so far at hand. Vendors' catalogue collections and MDDR as a source of potential or known "actives", respectively, have been used. With the results reported herein, a set of ranges, mean values and standard deviations for several query parameters are presented in order to set a reference guide for the users. Applications on how to use this information in FT query building are also provided, using a newly built 3D-pharmacophore from 57 5HT-1F agonists and a published one which was used for virtual screening for tRNA-guanine transglycosylase (TGT) inhibitors.
Scalable Performance Measurement and Analysis
Energy Technology Data Exchange (ETDEWEB)
Gamblin, Todd [Univ. of North Carolina, Chapel Hill, NC (United States)
2009-01-01
Concurrency levels in large-scale, distributed-memory supercomputers are rising exponentially. Modern machines may contain 100,000 or more microprocessor cores, and the largest of these, IBM's Blue Gene/L, contains over 200,000 cores. Future systems are expected to support millions of concurrent tasks. In this dissertation, we focus on efficient techniques for measuring and analyzing the performance of applications running on very large parallel machines. Tuning the performance of large-scale applications can be a subtle and time-consuming task because application developers must measure and interpret data from many independent processes. While the volume of the raw data scales linearly with the number of tasks in the running system, the number of tasks is growing exponentially, and data for even small systems quickly becomes unmanageable. Transporting performance data from so many processes over a network can perturb application performance and make measurements inaccurate, and storing such data would require a prohibitive amount of space. Moreover, even if it were stored, analyzing the data would be extremely time-consuming. In this dissertation, we present novel methods for reducing performance data volume. The first draws on multi-scale wavelet techniques from signal processing to compress systemwide, time-varying load-balance data. The second uses statistical sampling to select a small subset of running processes to generate low-volume traces. A third approach combines sampling and wavelet compression to stratify performance data adaptively at run-time and to reduce further the cost of sampled tracing. We have integrated these approaches into Libra, a toolset for scalable load-balance analysis. We present Libra and show how it can be used to analyze data from large scientific applications scalably.
Parallelization of the Physical-Space Statistical Analysis System (PSAS)
Larson, J. W.; Guo, J.; Lyster, P. M.
1999-01-01
Atmospheric data assimilation is a method of combining observations with model forecasts to produce a more accurate description of the atmosphere than the observations or forecast alone can provide. Data assimilation plays an increasingly important role in the study of climate and atmospheric chemistry. The NASA Data Assimilation Office (DAO) has developed the Goddard Earth Observing System Data Assimilation System (GEOS DAS) to create assimilated datasets. The core computational components of the GEOS DAS include the GEOS General Circulation Model (GCM) and the Physical-space Statistical Analysis System (PSAS). The need for timely validation of scientific enhancements to the data assimilation system poses computational demands that are best met by distributed parallel software. PSAS is implemented in Fortran 90 using object-based design principles. The analysis portions of the code solve two equations. The first of these is the "innovation" equation, which is solved on the unstructured observation grid using a preconditioned conjugate gradient (CG) method. The "analysis" equation is a transformation from the observation grid back to a structured grid, and is solved by a direct matrix-vector multiplication. Use of a factored-operator formulation reduces the computational complexity of both the CG solver and the matrix-vector multiplication, rendering the matrix-vector multiplications as a successive product of operators on a vector. Sparsity is introduced to these operators by partitioning the observations using an icosahedral decomposition scheme. PSAS builds a large (approx. 128MB) run-time database of parameters used in the calculation of these operators. Implementing a message passing parallel computing paradigm into an existing yet developing computational system as complex as PSAS is nontrivial. One of the technical challenges is balancing the requirements for computational reproducibility with the need for high performance. The problem of computational
Tucker Tensor analysis of Matern functions in spatial statistics
Litvinenko, Alexander
2018-03-09
In this work, we describe advanced numerical tools for working with multivariate functions and for the analysis of large data sets. These tools will drastically reduce the required computing time and the storage cost, and, therefore, will allow us to consider much larger data sets or finer meshes. Covariance matrices are crucial in spatio-temporal statistical tasks, but are often very expensive to compute and store, especially in 3D. Therefore, we approximate covariance functions by cheap surrogates in a low-rank tensor format. We apply the Tucker and canonical tensor decompositions to a family of Matern- and Slater-type functions with varying parameters and demonstrate numerically that their approximations exhibit exponentially fast convergence. We prove the exponential convergence of the Tucker and canonical approximations in tensor rank parameters. Several statistical operations are performed in this low-rank tensor format, including evaluating the conditional covariance matrix, spatially averaged estimation variance, computing a quadratic form, determinant, trace, loglikelihood, inverse, and Cholesky decomposition of a large covariance matrix. Low-rank tensor approximations reduce the computing and storage costs essentially. For example, the storage cost is reduced from an exponential O(n^d) to a linear scaling O(drn), where d is the spatial dimension, n is the number of mesh points in one direction, and r is the tensor rank. Prerequisites for applicability of the proposed techniques are the assumptions that the data, locations, and measurements lie on a tensor (axes-parallel) grid and that the covariance function depends on a distance, ||x-y||.
Performance in College Chemistry: a Statistical Comparison Using Gender and Jungian Personality Type
Greene, Susan V.; Wheeler, Henry R.; Riley, Wayne D.
This study sorted college introductory chemistry students by gender and Jungian personality type. It recognized differences from the general population distribution and statistically compared the students' grades with their Jungian personality types. Data from 577 female students indicated that ESFP (extroverted, sensory, feeling, perceiving) and ENFP (extroverted, intuitive, feeling, perceiving) profiles performed poorly at statistically significant levels when compared with the distribution of females enrolled in introductory chemistry. The comparable analysis using data from 422 male students indicated that the poorly performing male profiles were ISTP (introverted, sensory, thinking, perceiving) and ESTP (extroverted, sensory, thinking, perceiving). ESTJ (extroverted, sensory, thinking, judging) female students withdrew from the course at a statistically significant level. For both genders, INTJ (introverted, intuitive, thinking, judging) students were the best performers. By examining the documented characteristics of Jungian profiles that correspond with poorly performing students in chemistry, one may more effectively assist the learning process and the retention of these individuals in the fields of natural science, engineering, and technology.
Statistical margin to DNB safety analysis approach for LOFT
International Nuclear Information System (INIS)
Atkinson, S.A.
1982-01-01
A method was developed and used for LOFT thermal safety analysis to estimate the statistical margin to DNB for the hot rod, and to base safety analysis on desired DNB probability limits. This method is an advanced approach using response surface analysis methods, a very efficient experimental design, and a 2nd-order response surface equation with a 2nd-order error propagation analysis to define the MDNBR probability density function. Calculations for limiting transients were used in the response surface analysis thereby including transient interactions and trip uncertainties in the MDNBR probability density
Data analysis using the Gnu R system for statistical computation
Energy Technology Data Exchange (ETDEWEB)
Simone, James; /Fermilab
2011-07-01
R is a language system for statistical computation. It is widely used in statistics, bioinformatics, machine learning, data mining, quantitative finance, and the analysis of clinical drug trials. Among the advantages of R are: it has become the standard language for developing statistical techniques, it is being actively developed by a large and growing global user community, it is open source software, it is highly portable (Linux, OS-X and Windows), it has a built-in documentation system, it produces high quality graphics and it is easily extensible with over four thousand extension library packages available covering statistics and applications. This report gives a very brief introduction to R with some examples using lattice QCD simulation results. It then discusses the development of R packages designed for chi-square minimization fits for lattice n-pt correlation functions.
Statistical and Machine Learning Models to Predict Programming Performance
Bergin, Susan
2006-01-01
This thesis details a longitudinal study on factors that influence introductory programming success and on the development of machine learning models to predict incoming student performance. Although numerous studies have developed models to predict programming success, the models struggled to achieve high accuracy in predicting the likely performance of incoming students. Our approach overcomes this by providing a machine learning technique, using a set of three significant...
Statistical analysis of agarwood oil compounds in discriminating the ...
African Journals Online (AJOL)
Enhancing and improving the discrimination technique is the main aim to determine or grade the good quality of agarwood oil. In this paper, all statistical works were performed via SPSS software. Two parameters involved are abundance of compound (%) and quality of t agarwood oil either low or high quality. The result ...
Common pitfalls in statistical analysis: Linear regression analysis
Directory of Open Access Journals (Sweden)
Rakesh Aggarwal
2017-01-01
Full Text Available In a previous article in this series, we explained correlation analysis which describes the strength of relationship between two continuous variables. In this article, we deal with linear regression analysis which predicts the value of one continuous variable from another. We also discuss the assumptions and pitfalls associated with this analysis.
A novel statistic for genome-wide interaction analysis.
Directory of Open Access Journals (Sweden)
Xuesen Wu
2010-09-01
Full Text Available Although great progress in genome-wide association studies (GWAS has been made, the significant SNP associations identified by GWAS account for only a few percent of the genetic variance, leading many to question where and how we can find the missing heritability. There is increasing interest in genome-wide interaction analysis as a possible source of finding heritability unexplained by current GWAS. However, the existing statistics for testing interaction have low power for genome-wide interaction analysis. To meet challenges raised by genome-wide interactional analysis, we have developed a novel statistic for testing interaction between two loci (either linked or unlinked. The null distribution and the type I error rates of the new statistic for testing interaction are validated using simulations. Extensive power studies show that the developed statistic has much higher power to detect interaction than classical logistic regression. The results identified 44 and 211 pairs of SNPs showing significant evidence of interactions with FDR<0.001 and 0.001
Ensemble Solar Forecasting Statistical Quantification and Sensitivity Analysis: Preprint
Energy Technology Data Exchange (ETDEWEB)
Cheung, WanYin; Zhang, Jie; Florita, Anthony; Hodge, Bri-Mathias; Lu, Siyuan; Hamann, Hendrik F.; Sun, Qian; Lehman, Brad
2015-12-08
Uncertainties associated with solar forecasts present challenges to maintain grid reliability, especially at high solar penetrations. This study aims to quantify the errors associated with the day-ahead solar forecast parameters and the theoretical solar power output for a 51-kW solar power plant in a utility area in the state of Vermont, U.S. Forecasts were generated by three numerical weather prediction (NWP) models, including the Rapid Refresh, the High Resolution Rapid Refresh, and the North American Model, and a machine-learning ensemble model. A photovoltaic (PV) performance model was adopted to calculate theoretical solar power generation using the forecast parameters (e.g., irradiance, cell temperature, and wind speed). Errors of the power outputs were quantified using statistical moments and a suite of metrics, such as the normalized root mean squared error (NRMSE). In addition, the PV model's sensitivity to different forecast parameters was quantified and analyzed. Results showed that the ensemble model yielded forecasts in all parameters with the smallest NRMSE. The NRMSE of solar irradiance forecasts of the ensemble NWP model was reduced by 28.10% compared to the best of the three NWP models. Further, the sensitivity analysis indicated that the errors of the forecasted cell temperature attributed only approximately 0.12% to the NRMSE of the power output as opposed to 7.44% from the forecasted solar irradiance.
Statistical modelling of networked human-automation performance using working memory capacity.
Ahmed, Nisar; de Visser, Ewart; Shaw, Tyler; Mohamed-Ameen, Amira; Campbell, Mark; Parasuraman, Raja
2014-01-01
This study examines the challenging problem of modelling the interaction between individual attentional limitations and decision-making performance in networked human-automation system tasks. Analysis of real experimental data from a task involving networked supervision of multiple unmanned aerial vehicles by human participants shows that both task load and network message quality affect performance, but that these effects are modulated by individual differences in working memory (WM) capacity. These insights were used to assess three statistical approaches for modelling and making predictions with real experimental networked supervisory performance data: classical linear regression, non-parametric Gaussian processes and probabilistic Bayesian networks. It is shown that each of these approaches can help designers of networked human-automated systems cope with various uncertainties in order to accommodate future users by linking expected operating conditions and performance from real experimental data to observable cognitive traits like WM capacity. Practitioner Summary: Working memory (WM) capacity helps account for inter-individual variability in operator performance in networked unmanned aerial vehicle supervisory tasks. This is useful for reliable performance prediction near experimental conditions via linear models; robust statistical prediction beyond experimental conditions via Gaussian process models and probabilistic inference about unknown task conditions/WM capacities via Bayesian network models.
Statistical Compilation of the ICT Sector and Policy Analysis | CRDI ...
International Development Research Centre (IDRC) Digital Library (Canada)
Statistical Compilation of the ICT Sector and Policy Analysis. As the presence and influence of information and communication technologies (ICTs) continues to widen and deepen, so too does its impact on economic development. However, much work needs to be done before the linkages between economic development ...
Multivariate statistical analysis of major and trace element data for ...
African Journals Online (AJOL)
Multivariate statistical analysis of major and trace element data for niobium exploration in the peralkaline granites of the anorogenic ring-complex province of Nigeria. PO Ogunleye, EC Ike, I Garba. Abstract. No Abstract Available Journal of Mining and Geology Vol.40(2) 2004: 107-117. Full Text: EMAIL FULL TEXT EMAIL ...
Statistical Compilation of the ICT Sector and Policy Analysis | IDRC ...
International Development Research Centre (IDRC) Digital Library (Canada)
Statistical Compilation of the ICT Sector and Policy Analysis. As the presence and influence of information and communication technologies (ICTs) continues to widen and deepen, so too does its impact on economic development. However, much work needs to be done before the linkages between economic development ...
Statistical analysis of the BOIL program in RSYST-III
International Nuclear Information System (INIS)
Beck, W.; Hausch, H.J.
1978-11-01
The paper describes a statistical analysis in the RSYST-III program system. Using the example of the BOIL program, it is shown how the effects of inaccurate input data on the output data can be discovered. The existing possibilities of data generation, data handling, and data evaluation are outlined. (orig.) [de
Statistical analysis of thermal conductivity of nanofluid containing ...
Indian Academy of Sciences (India)
Thermal conductivity measurements of nanofluids were analysed via two-factor completely randomized design and comparison of data means is carried out with Duncan's multiple-range test. Statistical analysis of experimental data show that temperature and weight fraction have a reasonable impact on the thermal ...
Multivariate statistical analysis of precipitation chemistry in Northwestern Spain
International Nuclear Information System (INIS)
Prada-Sanchez, J.M.; Garcia-Jurado, I.; Gonzalez-Manteiga, W.; Fiestras-Janeiro, M.G.; Espada-Rios, M.I.; Lucas-Dominguez, T.
1993-01-01
149 samples of rainwater were collected in the proximity of a power station in northwestern Spain at three rainwater monitoring stations. The resulting data are analyzed using multivariate statistical techniques. Firstly, the Principal Component Analysis shows that there are three main sources of pollution in the area (a marine source, a rural source and an acid source). The impact from pollution from these sources on the immediate environment of the stations is studied using Factorial Discriminant Analysis. 8 refs., 7 figs., 11 tabs
Multivariate statistical analysis of precipitation chemistry in Northwestern Spain
Energy Technology Data Exchange (ETDEWEB)
Prada-Sanchez, J.M.; Garcia-Jurado, I.; Gonzalez-Manteiga, W.; Fiestras-Janeiro, M.G.; Espada-Rios, M.I.; Lucas-Dominguez, T. (University of Santiago, Santiago (Spain). Faculty of Mathematics, Dept. of Statistics and Operations Research)
1993-07-01
149 samples of rainwater were collected in the proximity of a power station in northwestern Spain at three rainwater monitoring stations. The resulting data are analyzed using multivariate statistical techniques. Firstly, the Principal Component Analysis shows that there are three main sources of pollution in the area (a marine source, a rural source and an acid source). The impact from pollution from these sources on the immediate environment of the stations is studied using Factorial Discriminant Analysis. 8 refs., 7 figs., 11 tabs.
Reducing bias in the analysis of counting statistics data
International Nuclear Information System (INIS)
Hammersley, A.P.; Antoniadis, A.
1997-01-01
In the analysis of counting statistics data it is common practice to estimate the variance of the measured data points as the data points themselves. This practice introduces a bias into the results of further analysis which may be significant, and under certain circumstances lead to false conclusions. In the case of normal weighted least squares fitting this bias is quantified and methods to avoid it are proposed. (orig.)
Testing the performance of a blind burst statistic
Energy Technology Data Exchange (ETDEWEB)
Vicere, A [Istituto di Fisica, Universita di Urbino (Italy); Calamai, G [Istituto Nazionale di Fisica Nucleare, Sez. Firenze/Urbino (Italy); Campagna, E [Istituto Nazionale di Fisica Nucleare, Sez. Firenze/Urbino (Italy); Conforto, G [Istituto di Fisica, Universita di Urbino (Italy); Cuoco, E [Istituto Nazionale di Fisica Nucleare, Sez. Firenze/Urbino (Italy); Dominici, P [Istituto di Fisica, Universita di Urbino (Italy); Fiori, I [Istituto di Fisica, Universita di Urbino (Italy); Guidi, G M [Istituto di Fisica, Universita di Urbino (Italy); Losurdo, G [Istituto Nazionale di Fisica Nucleare, Sez. Firenze/Urbino (Italy); Martelli, F [Istituto di Fisica, Universita di Urbino (Italy); Mazzoni, M [Istituto Nazionale di Fisica Nucleare, Sez. Firenze/Urbino (Italy); Perniola, B [Istituto di Fisica, Universita di Urbino (Italy); Stanga, R [Istituto Nazionale di Fisica Nucleare, Sez. Firenze/Urbino (Italy); Vetrano, F [Istituto di Fisica, Universita di Urbino (Italy)
2003-09-07
In this work, we estimate the performance of a method for the detection of burst events in the data produced by interferometric gravitational wave detectors. We compute the receiver operating characteristics in the specific case of a simulated noise having the spectral density expected for Virgo, using test signals taken from a library of possible waveforms emitted during the collapse of the core of type II supernovae.
STATCAT, Statistical Analysis of Parametric and Non-Parametric Data
International Nuclear Information System (INIS)
David, Hugh
1990-01-01
1 - Description of program or function: A suite of 26 programs designed to facilitate the appropriate statistical analysis and data handling of parametric and non-parametric data, using classical and modern univariate and multivariate methods. 2 - Method of solution: Data is read entry by entry, using a choice of input formats, and the resultant data bank is checked for out-of- range, rare, extreme or missing data. The completed STATCAT data bank can be treated by a variety of descriptive and inferential statistical methods, and modified, using other standard programs as required
Statistical analysis of absorptive laser damage in dielectric thin films
International Nuclear Information System (INIS)
Budgor, A.B.; Luria-Budgor, K.F.
1978-01-01
The Weibull distribution arises as an example of the theory of extreme events. It is commonly used to fit statistical data arising in the failure analysis of electrical components and in DC breakdown of materials. This distribution is employed to analyze time-to-damage and intensity-to-damage statistics obtained when irradiating thin film coated samples of SiO 2 , ZrO 2 , and Al 2 O 3 with tightly focused laser beams. The data used is furnished by Milam. The fit to the data is excellent; and least squared correlation coefficients greater than 0.9 are often obtained
Detecting errors in micro and trace analysis by using statistics
DEFF Research Database (Denmark)
Heydorn, K.
1993-01-01
By assigning a standard deviation to each step in an analytical method it is possible to predict the standard deviation of each analytical result obtained by this method. If the actual variability of replicate analytical results agrees with the expected, the analytical method is said...... to be in statistical control. Significant deviations between analytical results from different laboratories reveal the presence of systematic errors, and agreement between different laboratories indicate the absence of systematic errors. This statistical approach, referred to as the analysis of precision, was applied...
Multivariate statistical analysis of atom probe tomography data
International Nuclear Information System (INIS)
Parish, Chad M.; Miller, Michael K.
2010-01-01
The application of spectrum imaging multivariate statistical analysis methods, specifically principal component analysis (PCA), to atom probe tomography (APT) data has been investigated. The mathematical method of analysis is described and the results for two example datasets are analyzed and presented. The first dataset is from the analysis of a PM 2000 Fe-Cr-Al-Ti steel containing two different ultrafine precipitate populations. PCA properly describes the matrix and precipitate phases in a simple and intuitive manner. A second APT example is from the analysis of an irradiated reactor pressure vessel steel. Fine, nm-scale Cu-enriched precipitates having a core-shell structure were identified and qualitatively described by PCA. Advantages, disadvantages, and future prospects for implementing these data analysis methodologies for APT datasets, particularly with regard to quantitative analysis, are also discussed.
International Nuclear Information System (INIS)
Bates, G.; Bodine, S.; Carroll, T.; Keller, M.
1984-02-01
This report begins with an overview of the Data Acquisition System (DAS), which supports several of PPPL's experimental devices. Performance measurements which were taken on DAS and the tools used to make them are then described
Data management and statistical analysis for environmental assessment
International Nuclear Information System (INIS)
Wendelberger, J.R.; McVittie, T.I.
1995-01-01
Data management and statistical analysis for environmental assessment are important issues on the interface of computer science and statistics. Data collection for environmental decision making can generate large quantities of various types of data. A database/GIS system developed is described which provides efficient data storage as well as visualization tools which may be integrated into the data analysis process. FIMAD is a living database and GIS system. The system has changed and developed over time to meet the needs of the Los Alamos National Laboratory Restoration Program. The system provides a repository for data which may be accessed by different individuals for different purposes. The database structure is driven by the large amount and varied types of data required for environmental assessment. The integration of the database with the GIS system provides the foundation for powerful visualization and analysis capabilities
Explorations in statistics: the analysis of ratios and normalized data.
Curran-Everett, Douglas
2013-09-01
Learning about statistics is a lot like learning about science: the learning is more meaningful if you can actively explore. This ninth installment of Explorations in Statistics explores the analysis of ratios and normalized-or standardized-data. As researchers, we compute a ratio-a numerator divided by a denominator-to compute a proportion for some biological response or to derive some standardized variable. In each situation, we want to control for differences in the denominator when the thing we really care about is the numerator. But there is peril lurking in a ratio: only if the relationship between numerator and denominator is a straight line through the origin will the ratio be meaningful. If not, the ratio will misrepresent the true relationship between numerator and denominator. In contrast, regression techniques-these include analysis of covariance-are versatile: they can accommodate an analysis of the relationship between numerator and denominator when a ratio is useless.
Statistical analysis and interpolation of compositional data in materials science.
Pesenson, Misha Z; Suram, Santosh K; Gregoire, John M
2015-02-09
Compositional data are ubiquitous in chemistry and materials science: analysis of elements in multicomponent systems, combinatorial problems, etc., lead to data that are non-negative and sum to a constant (for example, atomic concentrations). The constant sum constraint restricts the sampling space to a simplex instead of the usual Euclidean space. Since statistical measures such as mean and standard deviation are defined for the Euclidean space, traditional correlation studies, multivariate analysis, and hypothesis testing may lead to erroneous dependencies and incorrect inferences when applied to compositional data. Furthermore, composition measurements that are used for data analytics may not include all of the elements contained in the material; that is, the measurements may be subcompositions of a higher-dimensional parent composition. Physically meaningful statistical analysis must yield results that are invariant under the number of composition elements, requiring the application of specialized statistical tools. We present specifics and subtleties of compositional data processing through discussion of illustrative examples. We introduce basic concepts, terminology, and methods required for the analysis of compositional data and utilize them for the spatial interpolation of composition in a sputtered thin film. The results demonstrate the importance of this mathematical framework for compositional data analysis (CDA) in the fields of materials science and chemistry.
International Nuclear Information System (INIS)
Potter, G.L.; Ellsaesser, H.W.; MacCracken, M.C.; Luther, F.M.
1978-06-01
Results from the zonal model indicate quite reasonable agreement with observation in terms of the parameters and processes that influence the radiation and energy balance calculations. The model produces zonal statistics similar to those from general circulation models, and has also been shown to produce similar responses in sensitivity studies. Further studies of model performance are planned, including: comparison with July data; comparison of temperature and moisture transport and wind fields for winter and summer months; and a tabulation of atmospheric energetics. Based on these preliminary performance studies, however, it appears that the zonal model can be used in conjunction with more complex models to help unravel the problems of understanding the processes governing present climate and climate change. As can be seen in the subsequent paper on model sensitivity studies, in addition to reduced cost of computation, the zonal model facilitates analysis of feedback mechanisms and simplifies analysis of the interactions between processes
Building the Community Online Resource for Statistical Seismicity Analysis (CORSSA)
Michael, A. J.; Wiemer, S.; Zechar, J. D.; Hardebeck, J. L.; Naylor, M.; Zhuang, J.; Steacy, S.; Corssa Executive Committee
2010-12-01
Statistical seismology is critical to the understanding of seismicity, the testing of proposed earthquake prediction and forecasting methods, and the assessment of seismic hazard. Unfortunately, despite its importance to seismology - especially to those aspects with great impact on public policy - statistical seismology is mostly ignored in the education of seismologists, and there is no central repository for the existing open-source software tools. To remedy these deficiencies, and with the broader goal to enhance the quality of statistical seismology research, we have begun building the Community Online Resource for Statistical Seismicity Analysis (CORSSA). CORSSA is a web-based educational platform that is authoritative, up-to-date, prominent, and user-friendly. We anticipate that the users of CORSSA will range from beginning graduate students to experienced researchers. More than 20 scientists from around the world met for a week in Zurich in May 2010 to kick-start the creation of CORSSA: the format and initial table of contents were defined; a governing structure was organized; and workshop participants began drafting articles. CORSSA materials are organized with respect to six themes, each containing between four and eight articles. The CORSSA web page, www.corssa.org, officially unveiled on September 6, 2010, debuts with an initial set of approximately 10 to 15 articles available online for viewing and commenting with additional articles to be added over the coming months. Each article will be peer-reviewed and will present a balanced discussion, including illustrative examples and code snippets. Topics in the initial set of articles will include: introductions to both CORSSA and statistical seismology, basic statistical tests and their role in seismology; understanding seismicity catalogs and their problems; basic techniques for modeling seismicity; and methods for testing earthquake predictability hypotheses. A special article will compare and review
CORSSA: Community Online Resource for Statistical Seismicity Analysis
Zechar, J. D.; Hardebeck, J. L.; Michael, A. J.; Naylor, M.; Steacy, S.; Wiemer, S.; Zhuang, J.
2011-12-01
Statistical seismology is critical to the understanding of seismicity, the evaluation of proposed earthquake prediction and forecasting methods, and the assessment of seismic hazard. Unfortunately, despite its importance to seismology-especially to those aspects with great impact on public policy-statistical seismology is mostly ignored in the education of seismologists, and there is no central repository for the existing open-source software tools. To remedy these deficiencies, and with the broader goal to enhance the quality of statistical seismology research, we have begun building the Community Online Resource for Statistical Seismicity Analysis (CORSSA, www.corssa.org). We anticipate that the users of CORSSA will range from beginning graduate students to experienced researchers. More than 20 scientists from around the world met for a week in Zurich in May 2010 to kick-start the creation of CORSSA: the format and initial table of contents were defined; a governing structure was organized; and workshop participants began drafting articles. CORSSA materials are organized with respect to six themes, each will contain between four and eight articles. CORSSA now includes seven articles with an additional six in draft form along with forums for discussion, a glossary, and news about upcoming meetings, special issues, and recent papers. Each article is peer-reviewed and presents a balanced discussion, including illustrative examples and code snippets. Topics in the initial set of articles include: introductions to both CORSSA and statistical seismology, basic statistical tests and their role in seismology; understanding seismicity catalogs and their problems; basic techniques for modeling seismicity; and methods for testing earthquake predictability hypotheses. We have also begun curating a collection of statistical seismology software packages.
DEFF Research Database (Denmark)
Ravn, Ole; Andersen, Nils Axel; Andersen, Thomas Timm
While working with the UR-10 robot arm, it has become apparent that some commands have undesired behaviour when operating the robot arm through a socket connection, sending one command at a time. This report is a collection of the results optained when testing the performance of the different...
Computerized statistical analysis with bootstrap method in nuclear medicine
International Nuclear Information System (INIS)
Zoccarato, O.; Sardina, M.; Zatta, G.; De Agostini, A.; Barbesti, S.; Mana, O.; Tarolo, G.L.
1988-01-01
Statistical analysis of data samples involves some hypothesis about the features of data themselves. The accuracy of these hypotheses can influence the results of statistical inference. Among the new methods of computer-aided statistical analysis, the bootstrap method appears to be one of the most powerful, thanks to its ability to reproduce many artificial samples starting from a single original sample and because it works without hypothesis about data distribution. The authors applied the bootstrap method to two typical situation of Nuclear Medicine Department. The determination of the normal range of serum ferritin, as assessed by radioimmunoassay and defined by the mean value ±2 standard deviations, starting from an experimental sample of small dimension, shows an unacceptable lower limit (ferritin plasmatic levels below zero). On the contrary, the results obtained by elaborating 5000 bootstrap samples gives ans interval of values (10.95 ng/ml - 72.87 ng/ml) corresponding to the normal ranges commonly reported. Moreover the authors applied the bootstrap method in evaluating the possible error associated with the correlation coefficient determined between left ventricular ejection fraction (LVEF) values obtained by first pass radionuclide angiocardiography with 99m Tc and 195m Au. The results obtained indicate a high degree of statistical correlation and give the range of r 2 values to be considered acceptable for this type of studies
Statistical analysis of the Ft. Calhoun reactor coolant pump system
International Nuclear Information System (INIS)
Heising, Carolyn D.
1998-01-01
In engineering science, statistical quality control techniques have traditionally been applied to control manufacturing processes. An application to commercial nuclear power plant maintenance and control is presented that can greatly improve plant safety. As a demonstration of such an approach to plant maintenance and control, a specific system is analyzed: the reactor coolant pumps (RCPs) of the Ft. Calhoun nuclear power plant. This research uses capability analysis, Shewhart X-bar, R-charts, canonical correlation methods, and design of experiments to analyze the process for the state of statistical control. The results obtained show that six out of ten parameters are under control specifications limits and four parameters are not in the state of statistical control. The analysis shows that statistical process control methods can be applied as an early warning system capable of identifying significant equipment problems well in advance of traditional control room alarm indicators Such a system would provide operators with ample time to respond to possible emergency situations and thus improve plant safety and reliability. (author)
Statistical analysis of the Ft. Calhoun reactor coolant pump system
International Nuclear Information System (INIS)
Patel, Bimal; Heising, C.D.
1997-01-01
In engineering science, statistical quality control techniques have traditionally been applied to control manufacturing processes. An application to commercial nuclear power plant maintenance and control is presented that can greatly improve plant safety. As a demonstration of such an approach, a specific system is analyzed: the reactor coolant pumps (RCPs) of the Ft. Calhoun nuclear power plant. This research uses capability analysis, Shewhart X-bar, R charts, canonical correlation methods, and design of experiments to analyze the process for the state of statistical control. The results obtained show that six out of ten parameters are under control specification limits and four parameters are not in the state of statistical control. The analysis shows that statistical process control methods can be applied as an early warning system capable of identifying significant equipment problems well in advance of traditional control room alarm indicators. Such a system would provide operators with ample time to respond to possible emergency situations and thus improve plant safety and reliability. (Author)
STATISTICAL ANALYSIS OF THE HEAVY NEUTRAL ATOMS MEASURED BY IBEX
International Nuclear Information System (INIS)
Park, Jeewoo; Kucharek, Harald; Möbius, Eberhard; Galli, André; Livadiotis, George; Fuselier, Steve A.; McComas, David J.
2015-01-01
We investigate the directional distribution of heavy neutral atoms in the heliosphere by using heavy neutral maps generated with the IBEX-Lo instrument over three years from 2009 to 2011. The interstellar neutral (ISN) O and Ne gas flow was found in the first-year heavy neutral map at 601 keV and its flow direction and temperature were studied. However, due to the low counting statistics, researchers have not treated the full sky maps in detail. The main goal of this study is to evaluate the statistical significance of each pixel in the heavy neutral maps to get a better understanding of the directional distribution of heavy neutral atoms in the heliosphere. Here, we examine three statistical analysis methods: the signal-to-noise filter, the confidence limit method, and the cluster analysis method. These methods allow us to exclude background from areas where the heavy neutral signal is statistically significant. These methods also allow the consistent detection of heavy neutral atom structures. The main emission feature expands toward lower longitude and higher latitude from the observational peak of the ISN O and Ne gas flow. We call this emission the extended tail. It may be an imprint of the secondary oxygen atoms generated by charge exchange between ISN hydrogen atoms and oxygen ions in the outer heliosheath
Conditional Probability Analysis: A Statistical Tool for Environmental Analysis.
The use and application of environmental conditional probability analysis (CPA) is relatively recent. The first presentation using CPA was made in 2002 at the New England Association of Environmental Biologists Annual Meeting in Newport. Rhode Island. CPA has been used since the...
Oravec, Heather Ann; Daniels, Christopher C.
2014-01-01
The National Aeronautics and Space Administration has been developing a novel docking system to meet the requirements of future exploration missions to low-Earth orbit and beyond. A dynamic gas pressure seal is located at the main interface between the active and passive mating components of the new docking system. This seal is designed to operate in the harsh space environment, but is also to perform within strict loading requirements while maintaining an acceptable level of leak rate. In this study, a candidate silicone elastomer seal was designed, and multiple subscale test articles were manufactured for evaluation purposes. The force required to fully compress each test article at room temperature was quantified and found to be below the maximum allowable load for the docking system. However, a significant amount of scatter was observed in the test results. Due to the stochastic nature of the mechanical performance of this candidate docking seal, a statistical process control technique was implemented to isolate unusual compression behavior from typical mechanical performance. The results of this statistical analysis indicated a lack of process control, suggesting a variation in the manufacturing phase of the process. Further investigation revealed that changes in the manufacturing molding process had occurred which may have influenced the mechanical performance of the seal. This knowledge improves the chance of this and future space seals to satisfy or exceed design specifications.
Statistics in experimental design, preprocessing, and analysis of proteomics data.
Jung, Klaus
2011-01-01
High-throughput experiments in proteomics, such as 2-dimensional gel electrophoresis (2-DE) and mass spectrometry (MS), yield usually high-dimensional data sets of expression values for hundreds or thousands of proteins which are, however, observed on only a relatively small number of biological samples. Statistical methods for the planning and analysis of experiments are important to avoid false conclusions and to receive tenable results. In this chapter, the most frequent experimental designs for proteomics experiments are illustrated. In particular, focus is put on studies for the detection of differentially regulated proteins. Furthermore, issues of sample size planning, statistical analysis of expression levels as well as methods for data preprocessing are covered.
Common pitfalls in statistical analysis: Odds versus risk
Ranganathan, Priya; Aggarwal, Rakesh; Pramesh, C. S.
2015-01-01
In biomedical research, we are often interested in quantifying the relationship between an exposure and an outcome. “Odds” and “Risk” are the most common terms which are used as measures of association between variables. In this article, which is the fourth in the series of common pitfalls in statistical analysis, we explain the meaning of risk and odds and the difference between the two. PMID:26623395
Statistical and machine learning approaches for network analysis
Dehmer, Matthias
2012-01-01
Explore the multidisciplinary nature of complex networks through machine learning techniques Statistical and Machine Learning Approaches for Network Analysis provides an accessible framework for structurally analyzing graphs by bringing together known and novel approaches on graph classes and graph measures for classification. By providing different approaches based on experimental data, the book uniquely sets itself apart from the current literature by exploring the application of machine learning techniques to various types of complex networks. Comprised of chapters written by internation
Statistical Challenges of Big Data Analysis in Medicine
Czech Academy of Sciences Publication Activity Database
Kalina, Jan
2015-01-01
Roč. 3, č. 1 (2015), s. 24-27 ISSN 1805-8698 R&D Projects: GA ČR GA13-23940S Grant - others:CESNET Development Fund(CZ) 494/2013 Institutional support: RVO:67985807 Keywords : big data * variable selection * classification * cluster analysis Subject RIV: BB - Applied Statistics, Operational Research http://www.ijbh.org/ijbh2015-1.pdf
Research and Development on Food Nutrition Statistical Analysis Software System
Du Li; Ke Yun
2013-01-01
Designing and developing a set of food nutrition component statistical analysis software can realize the automation of nutrition calculation, improve the nutrition processional professional’s working efficiency and achieve the informatization of the nutrition propaganda and education. In the software development process, the software engineering method and database technology are used to calculate the human daily nutritional intake and the intelligent system is used to evaluate the user’s hea...
Maximum Likelihood, Consistency and Data Envelopment Analysis: A Statistical Foundation
Rajiv D. Banker
1993-01-01
This paper provides a formal statistical basis for the efficiency evaluation techniques of data envelopment analysis (DEA). DEA estimators of the best practice monotone increasing and concave production function are shown to be also maximum likelihood estimators if the deviation of actual output from the efficient output is regarded as a stochastic variable with a monotone decreasing probability density function. While the best practice frontier estimator is biased below the theoretical front...
Lifetime statistics of quantum chaos studied by a multiscale analysis
Di Falco, A.
2012-04-30
In a series of pump and probe experiments, we study the lifetime statistics of a quantum chaotic resonator when the number of open channels is greater than one. Our design embeds a stadium billiard into a two dimensional photonic crystal realized on a silicon-on-insulator substrate. We calculate resonances through a multiscale procedure that combines energy landscape analysis and wavelet transforms. Experimental data is found to follow the universal predictions arising from random matrix theory with an excellent level of agreement.
Statistical Analysis of the Exchange Rate of Bitcoin
Chu, Jeffrey; Nadarajah, Saralees; Chan, Stephen
2015-01-01
Bitcoin, the first electronic payment system, is becoming a popular currency. We provide a statistical analysis of the log-returns of the exchange rate of Bitcoin versus the United States Dollar. Fifteen of the most popular parametric distributions in finance are fitted to the log-returns. The generalized hyperbolic distribution is shown to give the best fit. Predictions are given for future values of the exchange rate. PMID:26222702
Statistical Analysis of the Exchange Rate of Bitcoin.
Directory of Open Access Journals (Sweden)
Jeffrey Chu
Full Text Available Bitcoin, the first electronic payment system, is becoming a popular currency. We provide a statistical analysis of the log-returns of the exchange rate of Bitcoin versus the United States Dollar. Fifteen of the most popular parametric distributions in finance are fitted to the log-returns. The generalized hyperbolic distribution is shown to give the best fit. Predictions are given for future values of the exchange rate.
Statistical Analysis of the Exchange Rate of Bitcoin.
Chu, Jeffrey; Nadarajah, Saralees; Chan, Stephen
2015-01-01
Bitcoin, the first electronic payment system, is becoming a popular currency. We provide a statistical analysis of the log-returns of the exchange rate of Bitcoin versus the United States Dollar. Fifteen of the most popular parametric distributions in finance are fitted to the log-returns. The generalized hyperbolic distribution is shown to give the best fit. Predictions are given for future values of the exchange rate.
Australasian Resuscitation In Sepsis Evaluation trial statistical analysis plan.
Delaney, Anthony; Peake, Sandra L; Bellomo, Rinaldo; Cameron, Peter; Holdgate, Anna; Howe, Belinda; Higgins, Alisa; Presneill, Jeffrey; Webb, Steve
2013-10-01
The Australasian Resuscitation In Sepsis Evaluation (ARISE) study is an international, multicentre, randomised, controlled trial designed to evaluate the effectiveness of early goal-directed therapy compared with standard care for patients presenting to the ED with severe sepsis. In keeping with current practice, and taking into considerations aspects of trial design and reporting specific to non-pharmacologic interventions, this document outlines the principles and methods for analysing and reporting the trial results. The document is prepared prior to completion of recruitment into the ARISE study, without knowledge of the results of the interim analysis conducted by the data safety and monitoring committee and prior to completion of the two related international studies. The statistical analysis plan was designed by the ARISE chief investigators, and reviewed and approved by the ARISE steering committee. The data collected by the research team as specified in the study protocol, and detailed in the study case report form were reviewed. Information related to baseline characteristics, characteristics of delivery of the trial interventions, details of resuscitation and other related therapies, and other relevant data are described with appropriate comparisons between groups. The primary, secondary and tertiary outcomes for the study are defined, with description of the planned statistical analyses. A statistical analysis plan was developed, along with a trial profile, mock-up tables and figures. A plan for presenting baseline characteristics, microbiological and antibiotic therapy, details of the interventions, processes of care and concomitant therapies, along with adverse events are described. The primary, secondary and tertiary outcomes are described along with identification of subgroups to be analysed. A statistical analysis plan for the ARISE study has been developed, and is available in the public domain, prior to the completion of recruitment into the
Composition heterogeneity analysis for DUPIC fuel(I) - Statistical analysis
Energy Technology Data Exchange (ETDEWEB)
Choi, Hang Bok [Korea Atomic Energy Research Institute, Taejon (Korea)
1999-08-01
The fuel composition heterogeneity effect on reactor performance parameters was assessed by refueling simulations for three DUPIC fuel options of fuel composition heterogeneity control: the fissile content adjustment, the reactivity control by slightly enriched and depleted uranium, and the reactivity control by natural uranium. For each DUPIC fuel option, the simulations were performed using 30 heterogeneous fuel types which were determined by the agglomerative hierarchical clustering method. The heterogeneity effect was considered during the refueling simulation by randomly selecting fuel types for the refueling operation. The refueling simulations of the heterogeneous core have shown that the key performance parameters such as the maximum channel power (MCP), maximum bundle power (MBP), and channel power peaking factor (CPPF) are close to those of the core that has single fuel type. For the three DUPIC fuel options, the uncertainties of MCP, MBP, and CPPF due to the fuel composition heterogeneity are less than 0.6, 1.5 and 0.8%, respectively, including the uncertainty of the group-average fuel property. This study has shown that the three DUPIC fuel options reduces the composition heterogeneity effectively and the zone power control system has a sufficient margin to adjust the perturbations cased by the fuel composition heterogeneity. 15 refs., 28 figs.,10 tabs. (Author)
Waste package performance analysis
International Nuclear Information System (INIS)
Lester, D.H.; Stula, R.T.; Kirstein, B.E.
1982-01-01
A performance assessment model for multiple barrier packages containing unreprocessed spent fuel has been applied to several package designs. The resulting preliminary assessments were intended for use in making decisions about package development programs. A computer model called BARIER estimates the package life and subsequent rate of release of selected nuclides. The model accounts for temperature, pressure (and resulting stresses), bulk and localized corrosion, and nuclide retardation by the backfill after water intrusion into the waste form. The assessment model assumes a post-closure, flooded, geologic repository. Calculations indicated that, within the bounds of model assumptions, packages could last for several hundred years. Intact backfills of appropriate design may be capable of nuclide release delay times on the order of 10 7 yr for uranium, plutonium, and americium. 8 references, 6 figures, 9 tables
Neutron activation and statistical analysis of pottery from Thera, Greece
International Nuclear Information System (INIS)
Kilikoglou, V.; Grimanis, A.P.; Karayannis, M.I.
1990-01-01
Neutron activation analysis, in combination with multivariate analysis of the generated data, was used for the chemical characterization of prehistoric pottery from the Greek islands of Thera, Melos (islands with similar geology) and Crete. The statistical procedure which proved that Theran pottery could be distinguished from Melian is described. This discrimination, attained for the first time, was mainly based on the concentrations of the trace elements Sm, Yb, Lu and Cr. Also, Cretan imports to both Thera and Melos were clearly separable from local products. (author) 22 refs.; 1 fig.; 4 tabs
Statistical Analysis of Hypercalcaemia Data related to Transferability
DEFF Research Database (Denmark)
Frølich, Anne; Nielsen, Bo Friis
2005-01-01
In this report we describe statistical analysis related to a study of hypercalcaemia carried out in the Copenhagen area in the ten year period from 1984 to 1994. Results from the study have previously been publised in a number of papers [3, 4, 5, 6, 7, 8, 9] and in various abstracts and posters...... at conferences during the late eighties and early nineties. In this report we give a more detailed description of many of the analysis and provide some new results primarily by simultaneous studies of several databases....
Statistical analysis of lightning electric field measured under Malaysian condition
Salimi, Behnam; Mehranzamir, Kamyar; Abdul-Malek, Zulkurnain
2014-02-01
Lightning is an electrical discharge during thunderstorms that can be either within clouds (Inter-Cloud), or between clouds and ground (Cloud-Ground). The Lightning characteristics and their statistical information are the foundation for the design of lightning protection system as well as for the calculation of lightning radiated fields. Nowadays, there are various techniques to detect lightning signals and to determine various parameters produced by a lightning flash. Each technique provides its own claimed performances. In this paper, the characteristics of captured broadband electric fields generated by cloud-to-ground lightning discharges in South of Malaysia are analyzed. A total of 130 cloud-to-ground lightning flashes from 3 separate thunderstorm events (each event lasts for about 4-5 hours) were examined. Statistical analyses of the following signal parameters were presented: preliminary breakdown pulse train time duration, time interval between preliminary breakdowns and return stroke, multiplicity of stroke, and percentages of single stroke only. The BIL model is also introduced to characterize the lightning signature patterns. Observations on the statistical analyses show that about 79% of lightning signals fit well with the BIL model. The maximum and minimum of preliminary breakdown time duration of the observed lightning signals are 84 ms and 560 us, respectively. The findings of the statistical results show that 7.6% of the flashes were single stroke flashes, and the maximum number of strokes recorded was 14 multiple strokes per flash. A preliminary breakdown signature in more than 95% of the flashes can be identified.
Analysis of Preference Data Using Intermediate Test Statistic Abstract
African Journals Online (AJOL)
PROF. O. E. OSUAGWU
2013-06-01
Jun 1, 2013 ... West African Journal of Industrial and Academic Research Vol.7 No. 1 June ... Keywords:-Preference data, Friedman statistic, multinomial test statistic, intermediate test statistic. ... new method and consequently a new statistic ...
Statistical Analysis of 30 Years Rainfall Data: A Case Study
Arvind, G.; Ashok Kumar, P.; Girish Karthi, S.; Suribabu, C. R.
2017-07-01
Rainfall is a prime input for various engineering design such as hydraulic structures, bridges and culverts, canals, storm water sewer and road drainage system. The detailed statistical analysis of each region is essential to estimate the relevant input value for design and analysis of engineering structures and also for crop planning. A rain gauge station located closely in Trichy district is selected for statistical analysis where agriculture is the prime occupation. The daily rainfall data for a period of 30 years is used to understand normal rainfall, deficit rainfall, Excess rainfall and Seasonal rainfall of the selected circle headquarters. Further various plotting position formulae available is used to evaluate return period of monthly, seasonally and annual rainfall. This analysis will provide useful information for water resources planner, farmers and urban engineers to assess the availability of water and create the storage accordingly. The mean, standard deviation and coefficient of variation of monthly and annual rainfall was calculated to check the rainfall variability. From the calculated results, the rainfall pattern is found to be erratic. The best fit probability distribution was identified based on the minimum deviation between actual and estimated values. The scientific results and the analysis paved the way to determine the proper onset and withdrawal of monsoon results which were used for land preparation and sowing.
Validation of statistical models for creep rupture by parametric analysis
Energy Technology Data Exchange (ETDEWEB)
Bolton, J., E-mail: john.bolton@uwclub.net [65, Fisher Ave., Rugby, Warks CV22 5HW (United Kingdom)
2012-01-15
Statistical analysis is an efficient method for the optimisation of any candidate mathematical model of creep rupture data, and for the comparative ranking of competing models. However, when a series of candidate models has been examined and the best of the series has been identified, there is no statistical criterion to determine whether a yet more accurate model might be devised. Hence there remains some uncertainty that the best of any series examined is sufficiently accurate to be considered reliable as a basis for extrapolation. This paper proposes that models should be validated primarily by parametric graphical comparison to rupture data and rupture gradient data. It proposes that no mathematical model should be considered reliable for extrapolation unless the visible divergence between model and data is so small as to leave no apparent scope for further reduction. This study is based on the data for a 12% Cr alloy steel used in BS PD6605:1998 to exemplify its recommended statistical analysis procedure. The models considered in this paper include a) a relatively simple model, b) the PD6605 recommended model and c) a more accurate model of somewhat greater complexity. - Highlights: Black-Right-Pointing-Pointer The paper discusses the validation of creep rupture models derived from statistical analysis. Black-Right-Pointing-Pointer It demonstrates that models can be satisfactorily validated by a visual-graphic comparison of models to data. Black-Right-Pointing-Pointer The method proposed utilises test data both as conventional rupture stress and as rupture stress gradient. Black-Right-Pointing-Pointer The approach is shown to be more reliable than a well-established and widely used method (BS PD6605).
Comparative Analysis of Kernel Methods for Statistical Shape Learning
National Research Council Canada - National Science Library
Rathi, Yogesh; Dambreville, Samuel; Tannenbaum, Allen
2006-01-01
.... In this work, we perform a comparative analysis of shape learning techniques such as linear PCA, kernel PCA, locally linear embedding and propose a new method, kernelized locally linear embedding...
Chan, Kar-Man; Yue, Grace Gar-Lee; Li, Ping; Wong, Eric Chun-Wai; Lee, Julia Kin-Ming; Kennelly, Edward J; Lau, Clara Bik-San
2017-03-03
According to Chinese Pharmacopoeia 2015 edition, Ganoderma (Lingzhi) is a species complex that comprise of Ganoderma lucidum and Ganoderma sinense. The bioactivity and chemical composition of G. lucidium had been studied extensively, and it was shown to possess antitumor activities in pharmacological studies. In contrast, G. sinense has not been studied in great detail. Our previous studies found that the stipe of G. sinense exhibited more potent antitumor activity than the pileus. To identify the antitumor compounds in the stipe of G. sinense, we studied its chemical components by merging the bioactivity results with liquid chromatography-mass spectrometry-based chemometrics. The stipe of G. sinense was extracted with water, followed by ethanol precipitation and liquid-liquid partition. The resulting residue was fractionated using column chromatography. The antitumor activity of these fractions were analysed using MTT assay in murine breast tumor 4T1 cells, and their chemical components were studied using the LC-QTOF-MS with multivariate statistical tools. The chemometric and MS/MS analysis correlated bioactivity with five known cytotoxic compounds, 4-hyroxyphenylacetate, 9-oxo-(10E,12E)-octadecadienoic acid, 3-phenyl-2-propenoic acid, 13-oxo-(9E,11E)-octadecadienoic acid and lingzhine C, from the stipe of G. sinense. To the best of our knowledge, 4-hyroxyphenylacetate, 3-phenyl-2-propenoic acid and lingzhine C are firstly reported to be found in G. sinense. These five compounds will be investigated for their antitumor activities in the future. Copyright © 2017 Elsevier B.V. All rights reserved.
Performance analysis of switching systems
Berg, van den R.A.
2008-01-01
Performance analysis is an important aspect in the design of dynamic (control) systems. Without a proper analysis of the behavior of a system, it is impossible to guarantee that a certain design satisfies the system’s requirements. For linear time-invariant systems, accurate performance analyses are
Multivariate statistical analysis a high-dimensional approach
Serdobolskii, V
2000-01-01
In the last few decades the accumulation of large amounts of in formation in numerous applications. has stimtllated an increased in terest in multivariate analysis. Computer technologies allow one to use multi-dimensional and multi-parametric models successfully. At the same time, an interest arose in statistical analysis with a de ficiency of sample data. Nevertheless, it is difficult to describe the recent state of affairs in applied multivariate methods as satisfactory. Unimprovable (dominating) statistical procedures are still unknown except for a few specific cases. The simplest problem of estimat ing the mean vector with minimum quadratic risk is unsolved, even for normal distributions. Commonly used standard linear multivari ate procedures based on the inversion of sample covariance matrices can lead to unstable results or provide no solution in dependence of data. Programs included in standard statistical packages cannot process 'multi-collinear data' and there are no theoretical recommen ...
Statistical methods for data analysis in particle physics
Lista, Luca
2017-01-01
This concise set of course-based notes provides the reader with the main concepts and tools needed to perform statistical analyses of experimental data, in particular in the field of high-energy physics (HEP). First, the book provides an introduction to probability theory and basic statistics, mainly intended as a refresher from readers’ advanced undergraduate studies, but also to help them clearly distinguish between the Frequentist and Bayesian approaches and interpretations in subsequent applications. More advanced concepts and applications are gradually introduced, culminating in the chapter on both discoveries and upper limits, as many applications in HEP concern hypothesis testing, where the main goal is often to provide better and better limits so as to eventually be able to distinguish between competing hypotheses, or to rule out some of them altogether. Many worked-out examples will help newcomers to the field and graduate students alike understand the pitfalls involved in applying theoretical co...
Statistical wind analysis for near-space applications
Roney, Jason A.
2007-09-01
Statistical wind models were developed based on the existing observational wind data for near-space altitudes between 60 000 and 100 000 ft (18 30 km) above ground level (AGL) at two locations, Akon, OH, USA, and White Sands, NM, USA. These two sites are envisioned as playing a crucial role in the first flights of high-altitude airships. The analysis shown in this paper has not been previously applied to this region of the stratosphere for such an application. Standard statistics were compiled for these data such as mean, median, maximum wind speed, and standard deviation, and the data were modeled with Weibull distributions. These statistics indicated, on a yearly average, there is a lull or a “knee” in the wind between 65 000 and 72 000 ft AGL (20 22 km). From the standard statistics, trends at both locations indicated substantial seasonal variation in the mean wind speed at these heights. The yearly and monthly statistical modeling indicated that Weibull distributions were a reasonable model for the data. Forecasts and hindcasts were done by using a Weibull model based on 2004 data and comparing the model with the 2003 and 2005 data. The 2004 distribution was also a reasonable model for these years. Lastly, the Weibull distribution and cumulative function were used to predict the 50%, 95%, and 99% winds, which are directly related to the expected power requirements of a near-space station-keeping airship. These values indicated that using only the standard deviation of the mean may underestimate the operational conditions.
STATISTICAL ANALYSIS OF SPORT MOVEMENT OBSERVATIONS: THE CASE OF ORIENTEERING
Directory of Open Access Journals (Sweden)
K. Amouzandeh
2017-09-01
Full Text Available Study of movement observations is becoming more popular in several applications. Particularly, analyzing sport movement time series has been considered as a demanding area. However, most of the attempts made on analyzing movement sport data have focused on spatial aspects of movement to extract some movement characteristics, such as spatial patterns and similarities. This paper proposes statistical analysis of sport movement observations, which refers to analyzing changes in the spatial movement attributes (e.g. distance, altitude and slope and non-spatial movement attributes (e.g. speed and heart rate of athletes. As the case study, an example dataset of movement observations acquired during the “orienteering” sport is presented and statistically analyzed.
Noise removing in encrypted color images by statistical analysis
Islam, N.; Puech, W.
2012-03-01
Cryptographic techniques are used to secure confidential data from unauthorized access but these techniques are very sensitive to noise. A single bit change in encrypted data can have catastrophic impact over the decrypted data. This paper addresses the problem of removing bit error in visual data which are encrypted using AES algorithm in the CBC mode. In order to remove the noise, a method is proposed which is based on the statistical analysis of each block during the decryption. The proposed method exploits local statistics of the visual data and confusion/diffusion properties of the encryption algorithm to remove the errors. Experimental results show that the proposed method can be used at the receiving end for the possible solution for noise removing in visual data in encrypted domain.
Statistical Analysis Of Failure Strength Of Material Using Weibull Distribution
International Nuclear Information System (INIS)
Entin Hartini; Mike Susmikanti; Antonius Sitompul
2008-01-01
In evaluation of ceramic and glass materials strength a statistical approach is necessary Strength of ceramic and glass depend on its measure and size distribution of flaws in these material. The distribution of strength for ductile material is narrow and close to a Gaussian distribution while strength of brittle materials as ceramic and glass following Weibull distribution. The Weibull distribution is an indicator of the failure of material strength resulting from a distribution of flaw size. In this paper, cumulative probability of material strength to failure probability, cumulative probability of failure versus fracture stress and cumulative probability of reliability of material were calculated. Statistical criteria calculation supporting strength analysis of Silicon Nitride material were done utilizing MATLAB. (author)
Multivariate statistical pattern recognition system for reactor noise analysis
International Nuclear Information System (INIS)
Gonzalez, R.C.; Howington, L.C.; Sides, W.H. Jr.; Kryter, R.C.
1976-01-01
A multivariate statistical pattern recognition system for reactor noise analysis was developed. The basis of the system is a transformation for decoupling correlated variables and algorithms for inferring probability density functions. The system is adaptable to a variety of statistical properties of the data, and it has learning, tracking, and updating capabilities. System design emphasizes control of the false-alarm rate. The ability of the system to learn normal patterns of reactor behavior and to recognize deviations from these patterns was evaluated by experiments at the ORNL High-Flux Isotope Reactor (HFIR). Power perturbations of less than 0.1 percent of the mean value in selected frequency ranges were detected by the system
Reactor noise analysis by statistical pattern recognition methods
International Nuclear Information System (INIS)
Howington, L.C.; Gonzalez, R.C.
1976-01-01
A multivariate statistical pattern recognition system for reactor noise analysis is presented. The basis of the system is a transformation for decoupling correlated variables and algorithms for inferring probability density functions. The system is adaptable to a variety of statistical properties of the data, and it has learning, tracking, updating, and data compacting capabilities. System design emphasizes control of the false-alarm rate. Its abilities to learn normal patterns, to recognize deviations from these patterns, and to reduce the dimensionality of data with minimum error were evaluated by experiments at the Oak Ridge National Laboratory (ORNL) High-Flux Isotope Reactor. Power perturbations of less than 0.1 percent of the mean value in selected frequency ranges were detected by the pattern recognition system
Multivariate statistical pattern recognition system for reactor noise analysis
International Nuclear Information System (INIS)
Gonzalez, R.C.; Howington, L.C.; Sides, W.H. Jr.; Kryter, R.C.
1975-01-01
A multivariate statistical pattern recognition system for reactor noise analysis was developed. The basis of the system is a transformation for decoupling correlated variables and algorithms for inferring probability density functions. The system is adaptable to a variety of statistical properties of the data, and it has learning, tracking, and updating capabilities. System design emphasizes control of the false-alarm rate. The ability of the system to learn normal patterns of reactor behavior and to recognize deviations from these patterns was evaluated by experiments at the ORNL High-Flux Isotope Reactor (HFIR). Power perturbations of less than 0.1 percent of the mean value in selected frequency ranges were detected by the system. 19 references
Statistical Analysis of Sport Movement Observations: the Case of Orienteering
Amouzandeh, K.; Karimipour, F.
2017-09-01
Study of movement observations is becoming more popular in several applications. Particularly, analyzing sport movement time series has been considered as a demanding area. However, most of the attempts made on analyzing movement sport data have focused on spatial aspects of movement to extract some movement characteristics, such as spatial patterns and similarities. This paper proposes statistical analysis of sport movement observations, which refers to analyzing changes in the spatial movement attributes (e.g. distance, altitude and slope) and non-spatial movement attributes (e.g. speed and heart rate) of athletes. As the case study, an example dataset of movement observations acquired during the "orienteering" sport is presented and statistically analyzed.
Statistical Mechanics Analysis of ATP Binding to a Multisubunit Enzyme
International Nuclear Information System (INIS)
Zhang Yun-Xin
2014-01-01
Due to inter-subunit communication, multisubunit enzymes usually hydrolyze ATP in a concerted fashion. However, so far the principle of this process remains poorly understood. In this study, from the viewpoint of statistical mechanics, a simple model is presented. In this model, we assume that the binding of ATP will change the potential of the corresponding enzyme subunit, and the degree of this change depends on the state of its adjacent subunits. The probability of enzyme in a given state satisfies the Boltzmann's distribution. Although it looks much simple, this model can fit the recent experimental data of chaperonin TRiC/CCT well. From this model, the dominant state of TRiC/CCT can be obtained. This study provide a new way to understand biophysical processe by statistical mechanics analysis. (interdisciplinary physics and related areas of science and technology)
Statistical analysis of subjective preferences for video enhancement
Woods, Russell L.; Satgunam, PremNandhini; Bronstad, P. Matthew; Peli, Eli
2010-02-01
Measuring preferences for moving video quality is harder than for static images due to the fleeting and variable nature of moving video. Subjective preferences for image quality can be tested by observers indicating their preference for one image over another. Such pairwise comparisons can be analyzed using Thurstone scaling (Farrell, 1999). Thurstone (1927) scaling is widely used in applied psychology, marketing, food tasting and advertising research. Thurstone analysis constructs an arbitrary perceptual scale for the items that are compared (e.g. enhancement levels). However, Thurstone scaling does not determine the statistical significance of the differences between items on that perceptual scale. Recent papers have provided inferential statistical methods that produce an outcome similar to Thurstone scaling (Lipovetsky and Conklin, 2004). Here, we demonstrate that binary logistic regression can analyze preferences for enhanced video.
Statistical Analysis of Radio Propagation Channel in Ruins Environment
Directory of Open Access Journals (Sweden)
Jiao He
2015-01-01
Full Text Available The cellphone based localization system for search and rescue in complex high density ruins has attracted a great interest in recent years, where the radio channel characteristics are critical for design and development of such a system. This paper presents a spatial smoothing estimation via rotational invariance technique (SS-ESPRIT for radio channel characterization of high density ruins. The radio propagations at three typical mobile communication bands (0.9, 1.8, and 2 GHz are investigated in two different scenarios. Channel parameters, such as arrival time, delays, and complex amplitudes, are statistically analyzed. Furthermore, a channel simulator is built based on these statistics. By comparison analysis of average excess delay and delay spread, the validation results show a good agreement between the measurements and channel modeling results.
Sealed-bid auction of Netherlands mussels: statistical analysis
Kleijnen, J.P.C.; van Schaik, F.D.J.
2011-01-01
This article presents an econometric analysis of the many data on the sealed-bid auction that sells mussels in Yerseke town, the Netherlands. The goals of this analysis are obtaining insight into the important factors that determine the price of these mussels, and quantifying the performance of an
Statistical analysis of the spatial distribution of galaxies and clusters
International Nuclear Information System (INIS)
Cappi, Alberto
1993-01-01
This thesis deals with the analysis of the distribution of galaxies and clusters, describing some observational problems and statistical results. First chapter gives a theoretical introduction, aiming to describe the framework of the formation of structures, tracing the history of the Universe from the Planck time, t_p = 10"-"4"3 sec and temperature corresponding to 10"1"9 GeV, to the present epoch. The most usual statistical tools and models of the galaxy distribution, with their advantages and limitations, are described in chapter two. A study of the main observed properties of galaxy clustering, together with a detailed statistical analysis of the effects of selecting galaxies according to apparent magnitude or diameter, is reported in chapter three. Chapter four delineates some properties of groups of galaxies, explaining the reasons of discrepant results on group distributions. Chapter five is a study of the distribution of galaxy clusters, with different statistical tools, like correlations, percolation, void probability function and counts in cells; it is found the same scaling-invariant behaviour of galaxies. Chapter six describes our finding that rich galaxy clusters too belong to the fundamental plane of elliptical galaxies, and gives a discussion of its possible implications. Finally chapter seven reviews the possibilities offered by multi-slit and multi-fibre spectrographs, and I present some observational work on nearby and distant galaxy clusters. In particular, I show the opportunities offered by ongoing surveys of galaxies coupled with multi-object fibre spectrographs, focusing on the ESO Key Programme A galaxy redshift survey in the south galactic pole region to which I collaborate and on MEFOS, a multi-fibre instrument with automatic positioning. Published papers related to the work described in this thesis are reported in the last appendix. (author) [fr
STATISTICAL ANALYSIS OF TANK 18F FLOOR SAMPLE RESULTS
Energy Technology Data Exchange (ETDEWEB)
Harris, S.
2010-09-02
Representative sampling has been completed for characterization of the residual material on the floor of Tank 18F as per the statistical sampling plan developed by Shine [1]. Samples from eight locations have been obtained from the tank floor and two of the samples were archived as a contingency. Six samples, referred to in this report as the current scrape samples, have been submitted to and analyzed by SRNL [2]. This report contains the statistical analysis of the floor sample analytical results to determine if further data are needed to reduce uncertainty. Included are comparisons with the prior Mantis samples results [3] to determine if they can be pooled with the current scrape samples to estimate the upper 95% confidence limits (UCL{sub 95%}) for concentration. Statistical analysis revealed that the Mantis and current scrape sample results are not compatible. Therefore, the Mantis sample results were not used to support the quantification of analytes in the residual material. Significant spatial variability among the current sample results was not found. Constituent concentrations were similar between the North and South hemispheres as well as between the inner and outer regions of the tank floor. The current scrape sample results from all six samples fall within their 3-sigma limits. In view of the results from numerous statistical tests, the data were pooled from all six current scrape samples. As such, an adequate sample size was provided for quantification of the residual material on the floor of Tank 18F. The uncertainty is quantified in this report by an upper 95% confidence limit (UCL{sub 95%}) on each analyte concentration. The uncertainty in analyte concentration was calculated as a function of the number of samples, the average, and the standard deviation of the analytical results. The UCL{sub 95%} was based entirely on the six current scrape sample results (each averaged across three analytical determinations).
Statistical Analysis Of Tank 19F Floor Sample Results
International Nuclear Information System (INIS)
Harris, S.
2010-01-01
Representative sampling has been completed for characterization of the residual material on the floor of Tank 19F as per the statistical sampling plan developed by Harris and Shine. Samples from eight locations have been obtained from the tank floor and two of the samples were archived as a contingency. Six samples, referred to in this report as the current scrape samples, have been submitted to and analyzed by SRNL. This report contains the statistical analysis of the floor sample analytical results to determine if further data are needed to reduce uncertainty. Included are comparisons with the prior Mantis samples results to determine if they can be pooled with the current scrape samples to estimate the upper 95% confidence limits (UCL95%) for concentration. Statistical analysis revealed that the Mantis and current scrape sample results are not compatible. Therefore, the Mantis sample results were not used to support the quantification of analytes in the residual material. Significant spatial variability among the current scrape sample results was not found. Constituent concentrations were similar between the North and South hemispheres as well as between the inner and outer regions of the tank floor. The current scrape sample results from all six samples fall within their 3-sigma limits. In view of the results from numerous statistical tests, the data were pooled from all six current scrape samples. As such, an adequate sample size was provided for quantification of the residual material on the floor of Tank 19F. The uncertainty is quantified in this report by an UCL95% on each analyte concentration. The uncertainty in analyte concentration was calculated as a function of the number of samples, the average, and the standard deviation of the analytical results. The UCL95% was based entirely on the six current scrape sample results (each averaged across three analytical determinations).
A laboratory evaluation of the influence of weighing gauges performance on extreme events statistics
Colli, Matteo; Lanza, Luca
2014-05-01
The effects of inaccurate ground based rainfall measurements on the information derived from rain records is yet not much documented in the literature. La Barbera et al. (2002) investigated the propagation of the systematic mechanic errors of tipping bucket type rain gauges (TBR) into the most common statistics of rainfall extremes, e.g. in the assessment of the return period T (or the related non-exceedance probability) of short-duration/high intensity events. Colli et al. (2012) and Lanza et al. (2012) extended the analysis to a 22-years long precipitation data set obtained from a virtual weighing type gauge (WG). The artificial WG time series was obtained basing on real precipitation data measured at the meteo-station of the University of Genova and modelling the weighing gauge output as a linear dynamic system. This approximation was previously validated with dedicated laboratory experiments and is based on the evidence that the accuracy of WG measurements under real world/time varying rainfall conditions is mainly affected by the dynamic response of the gauge (as revealed during the last WMO Field Intercomparison of Rainfall Intensity Gauges). The investigation is now completed by analyzing actual measurements performed by two common weighing gauges, the OTT Pluvio2 load-cell gauge and the GEONOR T-200 vibrating-wire gauge, since both these instruments demonstrated very good performance under previous constant flow rate calibration efforts. A laboratory dynamic rainfall generation system has been arranged and validated in order to simulate a number of precipitation events with variable reference intensities. Such artificial events were generated basing on real world rainfall intensity (RI) records obtained from the meteo-station of the University of Genova so that the statistical structure of the time series is preserved. The influence of the WG RI measurements accuracy on the associated extreme events statistics is analyzed by comparing the original intensity
Raunig, David L; McShane, Lisa M; Pennello, Gene; Gatsonis, Constantine; Carson, Paul L; Voyvodic, James T; Wahl, Richard L; Kurland, Brenda F; Schwarz, Adam J; Gönen, Mithat; Zahlmann, Gudrun; Kondratovich, Marina V; O'Donnell, Kevin; Petrick, Nicholas; Cole, Patricia E; Garra, Brian; Sullivan, Daniel C
2015-02-01
Technological developments and greater rigor in the quantitative measurement of biological features in medical images have given rise to an increased interest in using quantitative imaging biomarkers to measure changes in these features. Critical to the performance of a quantitative imaging biomarker in preclinical or clinical settings are three primary metrology areas of interest: measurement linearity and bias, repeatability, and the ability to consistently reproduce equivalent results when conditions change, as would be expected in any clinical trial. Unfortunately, performance studies to date differ greatly in designs, analysis method, and metrics used to assess a quantitative imaging biomarker for clinical use. It is therefore difficult or not possible to integrate results from different studies or to use reported results to design studies. The Radiological Society of North America and the Quantitative Imaging Biomarker Alliance with technical, radiological, and statistical experts developed a set of technical performance analysis methods, metrics, and study designs that provide terminology, metrics, and methods consistent with widely accepted metrological standards. This document provides a consistent framework for the conduct and evaluation of quantitative imaging biomarker performance studies so that results from multiple studies can be compared, contrasted, or combined. © The Author(s) 2014 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.
PVeStA: A Parallel Statistical Model Checking and Quantitative Analysis Tool
AlTurki, Musab
2011-01-01
Statistical model checking is an attractive formal analysis method for probabilistic systems such as, for example, cyber-physical systems which are often probabilistic in nature. This paper is about drastically increasing the scalability of statistical model checking, and making such scalability of analysis available to tools like Maude, where probabilistic systems can be specified at a high level as probabilistic rewrite theories. It presents PVeStA, an extension and parallelization of the VeStA statistical model checking tool [10]. PVeStA supports statistical model checking of probabilistic real-time systems specified as either: (i) discrete or continuous Markov Chains; or (ii) probabilistic rewrite theories in Maude. Furthermore, the properties that it can model check can be expressed in either: (i) PCTL/CSL, or (ii) the QuaTEx quantitative temporal logic. As our experiments show, the performance gains obtained from parallelization can be very high. © 2011 Springer-Verlag.
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...
International Conference on Modern Problems of Stochastic Analysis and Statistics
2017-01-01
This book brings together the latest findings in the area of stochastic analysis and statistics. The individual chapters cover a wide range of topics from limit theorems, Markov processes, nonparametric methods, acturial science, population dynamics, and many others. The volume is dedicated to Valentin Konakov, head of the International Laboratory of Stochastic Analysis and its Applications on the occasion of his 70th birthday. Contributions were prepared by the participants of the international conference of the international conference “Modern problems of stochastic analysis and statistics”, held at the Higher School of Economics in Moscow from May 29 - June 2, 2016. It offers a valuable reference resource for researchers and graduate students interested in modern stochastics.
Can We Use Polya’s Method to Improve Students’ Performance in the Statistics Classes?
Directory of Open Access Journals (Sweden)
Indika Wickramasinghe
2015-01-01
Full Text Available In this study, Polya’s problem-solving method is introduced in a statistics class in an effort to enhance students’ performance. Teaching the method was applied to one of the two introductory-level statistics classes taught by the same instructor, and a comparison was made between the performances in the two classes. The results indicate there was a significant improvement of the students’ performance in the class in which Polya’s method was introduced.
Consolidity analysis for fully fuzzy functions, matrices, probability and statistics
Directory of Open Access Journals (Sweden)
Walaa Ibrahim Gabr
2015-03-01
Full Text Available The paper presents a comprehensive review of the know-how for developing the systems consolidity theory for modeling, analysis, optimization and design in fully fuzzy environment. The solving of systems consolidity theory included its development for handling new functions of different dimensionalities, fuzzy analytic geometry, fuzzy vector analysis, functions of fuzzy complex variables, ordinary differentiation of fuzzy functions and partial fraction of fuzzy polynomials. On the other hand, the handling of fuzzy matrices covered determinants of fuzzy matrices, the eigenvalues of fuzzy matrices, and solving least-squares fuzzy linear equations. The approach demonstrated to be also applicable in a systematic way in handling new fuzzy probabilistic and statistical problems. This included extending the conventional probabilistic and statistical analysis for handling fuzzy random data. Application also covered the consolidity of fuzzy optimization problems. Various numerical examples solved have demonstrated that the new consolidity concept is highly effective in solving in a compact form the propagation of fuzziness in linear, nonlinear, multivariable and dynamic problems with different types of complexities. Finally, it is demonstrated that the implementation of the suggested fuzzy mathematics can be easily embedded within normal mathematics through building special fuzzy functions library inside the computational Matlab Toolbox or using other similar software languages.
Kleijnen, J.P.C.
1995-01-01
This tutorial discusses what-if analysis and optimization of System Dynamics models. These problems are solved, using the statistical techniques of regression analysis and design of experiments (DOE). These issues are illustrated by applying the statistical techniques to a System Dynamics model for
Signal processing and statistical analysis of spaced-based measurements
International Nuclear Information System (INIS)
Iranpour, K.
1996-05-01
The reports deals with data obtained by the ROSE rocket project. This project was designed to investigate the low altitude auroral instabilities in the electrojet region. The spectral and statistical analyses indicate the existence of unstable waves in the ionized gas in the region. An experimentally obtained dispersion relation for these waves were established. It was demonstrated that the characteristic phase velocities are much lower than what is expected from the standard theoretical results. This analysis of the ROSE data indicate the cascading of energy from lower to higher frequencies. 44 refs., 54 figs
Statistical Analysis of Designed Experiments Theory and Applications
Tamhane, Ajit C
2012-01-01
A indispensable guide to understanding and designing modern experiments The tools and techniques of Design of Experiments (DOE) allow researchers to successfully collect, analyze, and interpret data across a wide array of disciplines. Statistical Analysis of Designed Experiments provides a modern and balanced treatment of DOE methodology with thorough coverage of the underlying theory and standard designs of experiments, guiding the reader through applications to research in various fields such as engineering, medicine, business, and the social sciences. The book supplies a foundation for the
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....
Statistical analysis of anomalous transport in resistive interchange turbulence
International Nuclear Information System (INIS)
Sugama, Hideo; Wakatani, Masahiro.
1992-01-01
A new anomalous transport model for resistive interchange turbulence is derived from statistical analysis applying two-scale direct-interaction approximation to resistive magnetohydrodynamic equations with a gravity term. Our model is similar to the K-ε model for eddy viscosity of turbulent shear flows in that anomalous transport coefficients are expressed in terms of by the turbulent kinetic energy K and its dissipation rate ε while K and ε are determined by transport equations. This anomalous transport model can describe some nonlocal effects such as those from boundary conditions which cannot be treated by conventional models based on the transport coefficients represented by locally determined plasma parameters. (author)
Spatial Analysis Along Networks Statistical and Computational Methods
Okabe, Atsuyuki
2012-01-01
In the real world, there are numerous and various events that occur on and alongside networks, including the occurrence of traffic accidents on highways, the location of stores alongside roads, the incidence of crime on streets and the contamination along rivers. In order to carry out analyses of those events, the researcher needs to be familiar with a range of specific techniques. Spatial Analysis Along Networks provides a practical guide to the necessary statistical techniques and their computational implementation. Each chapter illustrates a specific technique, from Stochastic Point Process
Statistical analysis of the W Cyg light curve
International Nuclear Information System (INIS)
Klyus, I.A.
1983-01-01
A statistical analysis of the light curve of W Cygni has been carried out. The process of brightness variations brightness of the star is shown to be a stationary stochastic one. The hypothesis of stationarity of the process was checked at the significance level of α=0.05. Oscillations of the brightness with average durations of 131 and 250 days have been found. It is proved that oscillations are narrow-band noise, i.e. cycles. Peaks on the power spectrum corresponding to these cycles exceed 99% confidence interval. It has been stated that the oscillations are independent
Energy Technology Data Exchange (ETDEWEB)
Wallace, Jack, E-mail: jack.wallace@ce.queensu.ca [Department of Civil Engineering, Queen’s University, Ellis Hall, 58 University Avenue, Kingston, Ontario K7L 3N6 (Canada); Champagne, Pascale, E-mail: champagne@civil.queensu.ca [Department of Civil Engineering, Queen’s University, Ellis Hall, 58 University Avenue, Kingston, Ontario K7L 3N6 (Canada); Monnier, Anne-Charlotte, E-mail: anne-charlotte.monnier@insa-lyon.fr [National Institute for Applied Sciences – Lyon, 20 Avenue Albert Einstein, 69621 Villeurbanne Cedex (France)
2015-01-15
Highlights: • Performance of a hybrid passive landfill leachate treatment system was evaluated. • 33 Water chemistry parameters were sampled for 21 months and statistically analyzed. • Parameters were strongly linked and explained most (>40%) of the variation in data. • Alkalinity, ammonia, COD, heavy metals, and iron were criteria for performance. • Eight other parameters were key in modeling system dynamics and criteria. - Abstract: A pilot-scale hybrid-passive treatment system operated at the Merrick Landfill in North Bay, Ontario, Canada, treats municipal landfill leachate and provides for subsequent natural attenuation. Collected leachate is directed to a hybrid-passive treatment system, followed by controlled release to a natural attenuation zone before entering the nearby Little Sturgeon River. The study presents a comprehensive evaluation of the performance of the system using multivariate statistical techniques to determine the interactions between parameters, major pollutants in the leachate, and the biological and chemical processes occurring in the system. Five parameters (ammonia, alkalinity, chemical oxygen demand (COD), “heavy” metals of interest, with atomic weights above calcium, and iron) were set as criteria for the evaluation of system performance based on their toxicity to aquatic ecosystems and importance in treatment with respect to discharge regulations. System data for a full range of water quality parameters over a 21-month period were analyzed using principal components analysis (PCA), as well as principal components (PC) and partial least squares (PLS) regressions. PCA indicated a high degree of association for most parameters with the first PC, which explained a high percentage (>40%) of the variation in the data, suggesting strong statistical relationships among most of the parameters in the system. Regression analyses identified 8 parameters (set as independent variables) that were most frequently retained for modeling
Modeling of asphalt-rubber rotational viscosity by statistical analysis and neural networks
Directory of Open Access Journals (Sweden)
Luciano Pivoto Specht
2007-03-01
Full Text Available It is of a great importance to know binders' viscosity in order to perform handling, mixing, application processes and asphalt mixes compaction in highway surfacing. This paper presents the results of viscosity measurement in asphalt-rubber binders prepared in laboratory. The binders were prepared varying the rubber content, rubber particle size, duration and temperature of mixture, all following a statistical design plan. The statistical analysis and artificial neural networks were used to create mathematical models for prediction of the binders viscosity. The comparison between experimental data and simulated results with the generated models showed best performance of the neural networks analysis in contrast to the statistic models. The results indicated that the rubber content and duration of mixture have major influence on the observed viscosity for the considered interval of parameters variation.
Implementation of statistical analysis methods for medical physics data
International Nuclear Information System (INIS)
Teixeira, Marilia S.; Pinto, Nivia G.P.; Barroso, Regina C.; Oliveira, Luis F.
2009-01-01
The objective of biomedical research with different radiation natures is to contribute for the understanding of the basic physics and biochemistry of the biological systems, the disease diagnostic and the development of the therapeutic techniques. The main benefits are: the cure of tumors through the therapy, the anticipated detection of diseases through the diagnostic, the using as prophylactic mean for blood transfusion, etc. Therefore, for the better understanding of the biological interactions occurring after exposure to radiation, it is necessary for the optimization of therapeutic procedures and strategies for reduction of radioinduced effects. The group pf applied physics of the Physics Institute of UERJ have been working in the characterization of biological samples (human tissues, teeth, saliva, soil, plants, sediments, air, water, organic matrixes, ceramics, fossil material, among others) using X-rays diffraction and X-ray fluorescence. The application of these techniques for measurement, analysis and interpretation of the biological tissues characteristics are experimenting considerable interest in the Medical and Environmental Physics. All quantitative data analysis must be initiated with descriptive statistic calculation (means and standard deviations) in order to obtain a previous notion on what the analysis will reveal. It is well known que o high values of standard deviation found in experimental measurements of biologicals samples can be attributed to biological factors, due to the specific characteristics of each individual (age, gender, environment, alimentary habits, etc). This work has the main objective the development of a program for the use of specific statistic methods for the optimization of experimental data an analysis. The specialized programs for this analysis are proprietary, another objective of this work is the implementation of a code which is free and can be shared by the other research groups. As the program developed since the
Directory of Open Access Journals (Sweden)
Delphine Ribes
Full Text Available In this article we introduce JULIDE, a software toolkit developed to perform the 3D reconstruction, intensity normalization, volume standardization by 3D image registration and voxel-wise statistical analysis of autoradiographs of mouse brain sections. This software tool has been developed in the open-source ITK software framework and is freely available under a GPL license. The article presents the complete image processing chain from raw data acquisition to 3D statistical group analysis. Results of the group comparison in the context of a study on spatial learning are shown as an illustration of the data that can be obtained with this tool.
Statistical analysis of global horizontal solar irradiation GHI in Fez city, Morocco
Bounoua, Z.; Mechaqrane, A.
2018-05-01
An accurate knowledge of the solar energy reaching the ground is necessary for sizing and optimizing the performances of solar installations. This paper describes a statistical analysis of the global horizontal solar irradiation (GHI) at Fez city, Morocco. For better reliability, we have first applied a set of check procedures to test the quality of hourly GHI measurements. We then eliminate the erroneous values which are generally due to measurement or the cosine effect errors. Statistical analysis show that the annual mean daily values of GHI is of approximately 5 kWh/m²/day. Daily monthly mean values and other parameter are also calculated.
Abbey, Craig K.; Samuelson, Frank W.; Gallas, Brandon D.; Boone, John M.; Niklason, Loren T.
2013-03-01
The receiver operating characteristic (ROC) curve has become a common tool for evaluating diagnostic imaging technologies, and the primary endpoint of such evaluations is the area under the curve (AUC), which integrates sensitivity over the entire false positive range. An alternative figure of merit for ROC studies is expected utility (EU), which focuses on the relevant region of the ROC curve as defined by disease prevalence and the relative utility of the task. However if this measure is to be used, it must also have desirable statistical properties keep the burden of observer performance studies as low as possible. Here, we evaluate effect size and variability for EU and AUC. We use two observer performance studies recently submitted to the FDA to compare the EU and AUC endpoints. The studies were conducted using the multi-reader multi-case methodology in which all readers score all cases in all modalities. ROC curves from the study were used to generate both the AUC and EU values for each reader and modality. The EU measure was computed assuming an iso-utility slope of 1.03. We find mean effect sizes, the reader averaged difference between modalities, to be roughly 2.0 times as big for EU as AUC. The standard deviation across readers is roughly 1.4 times as large, suggesting better statistical properties for the EU endpoint. In a simple power analysis of paired comparison across readers, the utility measure required 36% fewer readers on average to achieve 80% statistical power compared to AUC.
Data analysis for radiological characterisation: Geostatistical and statistical complementarity
International Nuclear Information System (INIS)
Desnoyers, Yvon; Dubot, Didier
2012-01-01
Radiological characterisation may cover a large range of evaluation objectives during a decommissioning and dismantling (D and D) project: removal of doubt, delineation of contaminated materials, monitoring of the decontamination work and final survey. At each stage, collecting relevant data to be able to draw the conclusions needed is quite a big challenge. In particular two radiological characterisation stages require an advanced sampling process and data analysis, namely the initial categorization and optimisation of the materials to be removed and the final survey to demonstrate compliance with clearance levels. On the one hand the latter is widely used and well developed in national guides and norms, using random sampling designs and statistical data analysis. On the other hand a more complex evaluation methodology has to be implemented for the initial radiological characterisation, both for sampling design and for data analysis. The geostatistical framework is an efficient way to satisfy the radiological characterisation requirements providing a sound decision-making approach for the decommissioning and dismantling of nuclear premises. The relevance of the geostatistical methodology relies on the presence of a spatial continuity for radiological contamination. Thus geo-statistics provides reliable methods for activity estimation, uncertainty quantification and risk analysis, leading to a sound classification of radiological waste (surfaces and volumes). This way, the radiological characterization of contaminated premises can be divided into three steps. First, the most exhaustive facility analysis provides historical and qualitative information. Then, a systematic (exhaustive or not) surface survey of the contamination is implemented on a regular grid. Finally, in order to assess activity levels and contamination depths, destructive samples are collected at several locations within the premises (based on the surface survey results) and analysed. Combined with
Topics in statistical data analysis for high-energy physics
International Nuclear Information System (INIS)
Cowan, G.
2011-01-01
These lectures concert two topics that are becoming increasingly important in the analysis of high-energy physics data: Bayesian statistics and multivariate methods. In the Bayesian approach, we extend the interpretation of probability not only to cover the frequency of repeatable outcomes but also to include a degree of belief. In this way we are able to associate probability with a hypothesis and thus to answer directly questions that cannot be addressed easily with traditional frequentist methods. In multivariate analysis, we try to exploit as much information as possible from the characteristics that we measure for each event to distinguish between event types. In particular we will look at a method that has gained popularity in high-energy physics in recent years: the boosted decision tree. Finally, we give a brief sketch of how multivariate methods may be applied in a search for a new signal process. (author)
Using Statistical Analysis Software to Advance Nitro Plasticizer Wettability
Energy Technology Data Exchange (ETDEWEB)
Shear, Trevor Allan [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
2017-08-29
Statistical analysis in science is an extremely powerful tool that is often underutilized. Additionally, it is frequently the case that data is misinterpreted or not used to its fullest extent. Utilizing the advanced software JMP®, many aspects of experimental design and data analysis can be evaluated and improved. This overview will detail the features of JMP® and how they were used to advance a project, resulting in time and cost savings, as well as the collection of scientifically sound data. The project analyzed in this report addresses the inability of a nitro plasticizer to coat a gold coated quartz crystal sensor used in a quartz crystal microbalance. Through the use of the JMP® software, the wettability of the nitro plasticizer was increased by over 200% using an atmospheric plasma pen, ensuring good sample preparation and reliable results.
Statistical analysis of magnetically soft particles in magnetorheological elastomers
Gundermann, T.; Cremer, P.; Löwen, H.; Menzel, A. M.; Odenbach, S.
2017-04-01
The physical properties of magnetorheological elastomers (MRE) are a complex issue and can be influenced and controlled in many ways, e.g. by applying a magnetic field, by external mechanical stimuli, or by an electric potential. In general, the response of MRE materials to these stimuli is crucially dependent on the distribution of the magnetic particles inside the elastomer. Specific knowledge of the interactions between particles or particle clusters is of high relevance for understanding the macroscopic rheological properties and provides an important input for theoretical calculations. In order to gain a better insight into the correlation between the macroscopic effects and microstructure and to generate a database for theoretical analysis, x-ray micro-computed tomography (X-μCT) investigations as a base for a statistical analysis of the particle configurations were carried out. Different MREs with quantities of 2-15 wt% (0.27-2.3 vol%) of iron powder and different allocations of the particles inside the matrix were prepared. The X-μCT results were edited by an image processing software regarding the geometrical properties of the particles with and without the influence of an external magnetic field. Pair correlation functions for the positions of the particles inside the elastomer were calculated to statistically characterize the distributions of the particles in the samples.
Statistical analysis of installed wind capacity in the United States
International Nuclear Information System (INIS)
Staid, Andrea; Guikema, Seth D.
2013-01-01
There is a large disparity in the amount of wind power capacity installed in each of the states in the U.S. It is often thought that the different policies of individual state governments are the main reason for these differences, but this may not necessarily be the case. The aim of this paper is to use statistical methods to study the factors that have the most influence on the amount of installed wind capacity in each state. From this analysis, we were able to use these variables to accurately predict the installed wind capacity and to gain insight into the driving factors for wind power development and the reasons behind the differences among states. Using our best model, we find that the most important variables for explaining the amount of wind capacity have to do with the physical and geographic characteristics of the state as opposed to policies in place that favor renewable energy. - Highlights: • We conduct a statistical analysis of factors influencing wind capacity in the U.S. • We find that state policies do not strongly influence the differences among states. • Driving factors are wind resources, cropland area, and available percentage of land
Pattern recognition in menstrual bleeding diaries by statistical cluster analysis
Directory of Open Access Journals (Sweden)
Wessel Jens
2009-07-01
Full Text Available Abstract Background The aim of this paper is to empirically identify a treatment-independent statistical method to describe clinically relevant bleeding patterns by using bleeding diaries of clinical studies on various sex hormone containing drugs. Methods We used the four cluster analysis methods single, average and complete linkage as well as the method of Ward for the pattern recognition in menstrual bleeding diaries. The optimal number of clusters was determined using the semi-partial R2, the cubic cluster criterion, the pseudo-F- and the pseudo-t2-statistic. Finally, the interpretability of the results from a gynecological point of view was assessed. Results The method of Ward yielded distinct clusters of the bleeding diaries. The other methods successively chained the observations into one cluster. The optimal number of distinctive bleeding patterns was six. We found two desirable and four undesirable bleeding patterns. Cyclic and non cyclic bleeding patterns were well separated. Conclusion Using this cluster analysis with the method of Ward medications and devices having an impact on bleeding can be easily compared and categorized.
Statistical mechanical analysis of LMFBR fuel cladding tubes
International Nuclear Information System (INIS)
Poncelet, J.-P.; Pay, A.
1977-01-01
The most important design requirement on fuel pin cladding for LMFBR's is its mechanical integrity. Disruptive factors include internal pressure from mixed oxide fuel fission gas release, thermal stresses and high temperature creep, neutron-induced differential void-swelling as a source of stress in the cladding and irradiation creep of stainless steel material, corrosion by fission products. Under irradiation these load-restraining mechanisms are accentuated by stainless steel embrittlement and strength alterations. To account for the numerous uncertainties involved in the analysis by theoretical models and computer codes statistical tools are unavoidably requested, i.e. Monte Carlo simulation methods. Thanks to these techniques, uncertainties in nominal characteristics, material properties and environmental conditions can be linked up in a correct way and used for a more accurate conceptual design. First, a thermal creep damage index is set up through a sufficiently sophisticated clad physical analysis including arbitrary time dependence of power and neutron flux as well as effects of sodium temperature, burnup and steel mechanical behavior. Although this strain limit approach implies a more general but time consuming model., on the counterpart the net output is improved and e.g. clad temperature, stress and strain maxima may be easily assessed. A full spectrum of variables are statistically treated to account for their probability distributions. Creep damage probability may be obtained and can contribute to a quantitative fuel probability estimation
A Third Moment Adjusted Test Statistic for Small Sample Factor Analysis.
Lin, Johnny; Bentler, Peter M
2012-01-01
Goodness of fit testing in factor analysis is based on the assumption that the test statistic is asymptotically chi-square; but this property may not hold in small samples even when the factors and errors are normally distributed in the population. Robust methods such as Browne's asymptotically distribution-free method and Satorra Bentler's mean scaling statistic were developed under the presumption of non-normality in the factors and errors. This paper finds new application to the case where factors and errors are normally distributed in the population but the skewness of the obtained test statistic is still high due to sampling error in the observed indicators. An extension of Satorra Bentler's statistic is proposed that not only scales the mean but also adjusts the degrees of freedom based on the skewness of the obtained test statistic in order to improve its robustness under small samples. A simple simulation study shows that this third moment adjusted statistic asymptotically performs on par with previously proposed methods, and at a very small sample size offers superior Type I error rates under a properly specified model. Data from Mardia, Kent and Bibby's study of students tested for their ability in five content areas that were either open or closed book were used to illustrate the real-world performance of this statistic.
Notes on human performance analysis
International Nuclear Information System (INIS)
Hollnagel, E.; Pedersen, O.M.; Rasmussen, J.
1981-06-01
This paper contains a framework for the integration of observation and analysis of human performance in nuclear environments - real or simulated. It identifies four main sources of data, and describes the characteristic data types and methods of analysis for each source in relation to a common conceptual background. The general conclusion is that it is highly useful to combine the knowledge and experience from different contexts into coherent picture of how nuclear operators perform under varying circumstances. (author)
McCray, Wilmon Wil L., Jr.
The research was prompted by a need to conduct a study that assesses process improvement, quality management and analytical techniques taught to students in U.S. colleges and universities undergraduate and graduate systems engineering and the computing science discipline (e.g., software engineering, computer science, and information technology) degree programs during their academic training that can be applied to quantitatively manage processes for performance. Everyone involved in executing repeatable processes in the software and systems development lifecycle processes needs to become familiar with the concepts of quantitative management, statistical thinking, process improvement methods and how they relate to process-performance. Organizations are starting to embrace the de facto Software Engineering Institute (SEI) Capability Maturity Model Integration (CMMI RTM) Models as process improvement frameworks to improve business processes performance. High maturity process areas in the CMMI model imply the use of analytical, statistical, quantitative management techniques, and process performance modeling to identify and eliminate sources of variation, continually improve process-performance; reduce cost and predict future outcomes. The research study identifies and provides a detail discussion of the gap analysis findings of process improvement and quantitative analysis techniques taught in U.S. universities systems engineering and computing science degree programs, gaps that exist in the literature, and a comparison analysis which identifies the gaps that exist between the SEI's "healthy ingredients " of a process performance model and courses taught in U.S. universities degree program. The research also heightens awareness that academicians have conducted little research on applicable statistics and quantitative techniques that can be used to demonstrate high maturity as implied in the CMMI models. The research also includes a Monte Carlo simulation optimization
International Nuclear Information System (INIS)
Lacombe, J.P.
1985-12-01
Statistic study of Poisson non-homogeneous and spatial processes is the first part of this thesis. A Neyman-Pearson type test is defined concerning the intensity measurement of these processes. Conditions are given for which consistency of the test is assured, and others giving the asymptotic normality of the test statistics. Then some techniques of statistic processing of Poisson fields and their applications to a particle multidetector study are given. Quality tests of the device are proposed togetherwith signal extraction methods [fr
Sealed-Bid Auction of Dutch Mussels : Statistical Analysis
Kleijnen, J.P.C.; van Schaik, F.D.J.
2007-01-01
This article presents an econometric analysis of the many data on the sealed-bid auction that sells mussels in Yerseke town, the Netherlands. The goals of this analy- sis are obtaining insight into the important factors that determine the price of these mussels, and quantifying the performance of an
Statistical Analysis of Environmental Tritium around Wolsong Site
Energy Technology Data Exchange (ETDEWEB)
Kim, Ju Youl [FNC Technology Co., Yongin (Korea, Republic of)
2010-04-15
To find the relationship among airborne tritium, tritium in rainwater, TFWT (Tissue Free Water Tritium) and TBT (Tissue Bound Tritium), statistical analysis is conducted based on tritium data measured at KHNP employees' house around Wolsong nuclear power plants during 10 years from 1999 to 2008. The results show that tritium in such media exhibits a strong seasonal and annual periodicity. Tritium concentration in rainwater is observed to be highly correlated with TFWT and directly transmitted to TFWT without delay. The response of environmental radioactivity of tritium around Wolsong site is analyzed using time-series technique and non-parametric trend analysis. Tritium in the atmosphere and rainwater is strongly auto-correlated by seasonal and annual periodicity. TFWT concentration in pine needle is proven to be more sensitive to rainfall phenomenon than other weather variables. Non-parametric trend analysis of TFWT concentration within pine needle shows a increasing slope in terms of confidence level of 95%. This study demonstrates a usefulness of time-series and trend analysis for the interpretation of environmental radioactivity relationship with various environmental media.
performance performance analysis of gsm networks in minna
African Journals Online (AJOL)
eobe
in terms of key performance indicators (KPI) based on statistics performance indicators ... in this study. Keywords: GSM Network, Drive Test, KPI and Radio Frequency Network Optimization. 1. .... message (SMS) traffic or in scenarios where so.
Thermal Power Plant Performance Analysis
2012-01-01
The analysis of the reliability and availability of power plants is frequently based on simple indexes that do not take into account the criticality of some failures used for availability analysis. This criticality should be evaluated based on concepts of reliability which consider the effect of a component failure on the performance of the entire plant. System reliability analysis tools provide a root-cause analysis leading to the improvement of the plant maintenance plan. Taking in view that the power plant performance can be evaluated not only based on thermodynamic related indexes, such as heat-rate, Thermal Power Plant Performance Analysis focuses on the presentation of reliability-based tools used to define performance of complex systems and introduces the basic concepts of reliability, maintainability and risk analysis aiming at their application as tools for power plant performance improvement, including: · selection of critical equipment and components, · defini...
Statistical analysis of quality control of automatic processor
International Nuclear Information System (INIS)
Niu Yantao; Zhao Lei; Zhang Wei; Yan Shulin
2002-01-01
Objective: To strengthen the scientific management of automatic processor and promote QC, based on analyzing QC management chart for automatic processor by statistical method, evaluating and interpreting the data and trend of the chart. Method: Speed, contrast, minimum density of step wedge of film strip were measured everyday and recorded on the QC chart. Mean (x-bar), standard deviation (s) and range (R) were calculated. The data and the working trend were evaluated and interpreted for management decisions. Results: Using relative frequency distribution curve constructed by measured data, the authors can judge whether it is a symmetric bell-shaped curve or not. If not, it indicates a few extremes overstepping control limits possibly are pulling the curve to the left or right. If it is a normal distribution, standard deviation (s) is observed. When x-bar +- 2s lies in upper and lower control limits of relative performance indexes, it indicates the processor works in stable status in this period. Conclusion: Guided by statistical method, QC work becomes more scientific and quantified. The authors can deepen understanding and application of the trend chart, and improve the quality management to a new step
The R software fundamentals of programming and statistical analysis
Lafaye de Micheaux, Pierre; Liquet, Benoit
2013-01-01
The contents of The R Software are presented so as to be both comprehensive and easy for the reader to use. Besides its application as a self-learning text, this book can support lectures on R at any level from beginner to advanced. This book can serve as a textbook on R for beginners as well as more advanced users, working on Windows, MacOs or Linux OSes. The first part of the book deals with the heart of the R language and its fundamental concepts, including data organization, import and export, various manipulations, documentation, plots, programming and maintenance. The last chapter in this part deals with oriented object programming as well as interfacing R with C/C++ or Fortran, and contains a section on debugging techniques. This is followed by the second part of the book, which provides detailed explanations on how to perform many standard statistical analyses, mainly in the Biostatistics field. Topics from mathematical and statistical settings that are included are matrix operations, integration, o...
Predicting energy performance of a net-zero energy building: A statistical approach
International Nuclear Information System (INIS)
Kneifel, Joshua; Webb, David
2016-01-01
Highlights: • A regression model is applied to actual energy data from a net-zero energy building. • The model is validated through a rigorous statistical analysis. • Comparisons are made between model predictions and those of a physics-based model. • The model is a viable baseline for evaluating future models from the energy data. - Abstract: Performance-based building requirements have become more prevalent because it gives freedom in building design while still maintaining or exceeding the energy performance required by prescriptive-based requirements. In order to determine if building designs reach target energy efficiency improvements, it is necessary to estimate the energy performance of a building using predictive models and different weather conditions. Physics-based whole building energy simulation modeling is the most common approach. However, these physics-based models include underlying assumptions and require significant amounts of information in order to specify the input parameter values. An alternative approach to test the performance of a building is to develop a statistically derived predictive regression model using post-occupancy data that can accurately predict energy consumption and production based on a few common weather-based factors, thus requiring less information than simulation models. A regression model based on measured data should be able to predict energy performance of a building for a given day as long as the weather conditions are similar to those during the data collection time frame. This article uses data from the National Institute of Standards and Technology (NIST) Net-Zero Energy Residential Test Facility (NZERTF) to develop and validate a regression model to predict the energy performance of the NZERTF using two weather variables aggregated to the daily level, applies the model to estimate the energy performance of hypothetical NZERTFs located in different cities in the Mixed-Humid Climate Zone, and compares these
Analysis of neutron flux measurement systems using statistical functions
International Nuclear Information System (INIS)
Pontes, Eduardo Winston
1997-01-01
This work develops an integrated analysis for neutron flux measurement systems using the concepts of cumulants and spectra. Its major contribution is the generalization of Campbell's theorem in the form of spectra in the frequency domain, and its application to the analysis of neutron flux measurement systems. Campbell's theorem, in its generalized form, constitutes an important tool, not only to find the nth-order frequency spectra of the radiation detector, but also in the system analysis. The radiation detector, an ionization chamber for neutrons, is modeled for cylindrical, plane and spherical geometries. The detector current pulses are characterized by a vector of random parameters, and the associated charges, statistical moments and frequency spectra of the resulting current are calculated. A computer program is developed for application of the proposed methodology. In order for the analysis to integrate the associated electronics, the signal processor is studied, considering analog and digital configurations. The analysis is unified by developing the concept of equivalent systems that can be used to describe the cumulants and spectra in analog or digital systems. The noise in the signal processor input stage is analysed in terms of second order spectrum. Mathematical expressions are presented for cumulants and spectra up to fourth order, for important cases of filter positioning relative to detector spectra. Unbiased conventional estimators for cumulants are used, and, to evaluate systems precision and response time, expressions are developed for their variances. Finally, some possibilities for obtaining neutron radiation flux as a function of cumulants are discussed. In summary, this work proposes some analysis tools which make possible important decisions in the design of better neutron flux measurement systems. (author)
Log-Normality and Multifractal Analysis of Flame Surface Statistics
Saha, Abhishek; Chaudhuri, Swetaprovo; Law, Chung K.
2013-11-01
The turbulent flame surface is typically highly wrinkled and folded at a multitude of scales controlled by various flame properties. It is useful if the information contained in this complex geometry can be projected onto a simpler regular geometry for the use of spectral, wavelet or multifractal analyses. Here we investigate local flame surface statistics of turbulent flame expanding under constant pressure. First the statistics of local length ratio is experimentally obtained from high-speed Mie scattering images. For spherically expanding flame, length ratio on the measurement plane, at predefined equiangular sectors is defined as the ratio of the actual flame length to the length of a circular-arc of radius equal to the average radius of the flame. Assuming isotropic distribution of such flame segments we convolute suitable forms of the length-ratio probability distribution functions (pdfs) to arrive at corresponding area-ratio pdfs. Both the pdfs are found to be near log-normally distributed and shows self-similar behavior with increasing radius. Near log-normality and rather intermittent behavior of the flame-length ratio suggests similarity with dissipation rate quantities which stimulates multifractal analysis. Currently at Indian Institute of Science, India.
Statistical analysis of hydrologic data for Yucca Mountain
International Nuclear Information System (INIS)
Rutherford, B.M.; Hall, I.J.; Peters, R.R.; Easterling, R.G.; Klavetter, E.A.
1992-02-01
The geologic formations in the unsaturated zone at Yucca Mountain are currently being studied as the host rock for a potential radioactive waste repository. Data from several drill holes have been collected to provide the preliminary information needed for planning site characterization for the Yucca Mountain Project. Hydrologic properties have been measured on the core samples and the variables analyzed here are thought to be important in the determination of groundwater travel times. This report presents a statistical analysis of four hydrologic variables: saturated-matrix hydraulic conductivity, maximum moisture content, suction head, and calculated groundwater travel time. It is important to modelers to have as much information about the distribution of values of these variables as can be obtained from the data. The approach taken in this investigation is to (1) identify regions at the Yucca Mountain site that, according to the data, are distinctly different; (2) estimate the means and variances within these regions; (3) examine the relationships among the variables; and (4) investigate alternative statistical methods that might be applicable when more data become available. The five different functional stratigraphic units at three different locations are compared and grouped into relatively homogeneous regions. Within these regions, the expected values and variances associated with core samples of different sizes are estimated. The results provide a rough estimate of the distribution of hydrologic variables for small core sections within each region
Error analysis of terrestrial laser scanning data by means of spherical statistics and 3D graphs.
Cuartero, Aurora; Armesto, Julia; Rodríguez, Pablo G; Arias, Pedro
2010-01-01
This paper presents a complete analysis of the positional errors of terrestrial laser scanning (TLS) data based on spherical statistics and 3D graphs. Spherical statistics are preferred because of the 3D vectorial nature of the spatial error. Error vectors have three metric elements (one module and two angles) that were analyzed by spherical statistics. A study case has been presented and discussed in detail. Errors were calculating using 53 check points (CP) and CP coordinates were measured by a digitizer with submillimetre accuracy. The positional accuracy was analyzed by both the conventional method (modular errors analysis) and the proposed method (angular errors analysis) by 3D graphics and numerical spherical statistics. Two packages in R programming language were performed to obtain graphics automatically. The results indicated that the proposed method is advantageous as it offers a more complete analysis of the positional accuracy, such as angular error component, uniformity of the vector distribution, error isotropy, and error, in addition the modular error component by linear statistics.
LHCb: Statistical Comparison of CPU performance for LHCb applications on the Grid
Graciani, R
2009-01-01
The usage of CPU resources by LHCb on the Grid id dominated by two different applications: Gauss and Brunel. Gauss the application doing the Monte Carlo simulation of proton-proton collisions. Brunel is the application responsible for the reconstruction of the signals recorded by the detector converting them into objects that can be used for later physics analysis of the data (tracks, clusters,…) Both applications are based on the Gaudi and LHCb software frameworks. Gauss uses Pythia and Geant as underlying libraries for the simulation of the collision and the later passage of the generated particles through the LHCb detector. While Brunel makes use of LHCb specific code to process the data from each sub-detector. Both applications are CPU bound. Large Monte Carlo productions or data reconstructions running on the Grid are an ideal benchmark to compare the performance of the different CPU models for each case. Since the processed events are only statistically comparable, only statistical comparison of the...
Statistical analysis of Nomao customer votes for spots of France
Pálovics, Róbert; Daróczy, Bálint; Benczúr, András; Pap, Julia; Ermann, Leonardo; Phan, Samuel; Chepelianskii, Alexei D.; Shepelyansky, Dima L.
2015-08-01
We investigate the statistical properties of votes of customers for spots of France collected by the startup company Nomao. The frequencies of votes per spot and per customer are characterized by a power law distribution which remains stable on a time scale of a decade when the number of votes is varied by almost two orders of magnitude. Using the computer science methods we explore the spectrum and the eigenvalues of a matrix containing user ratings to geolocalized items. Eigenvalues nicely map to large towns and regions but show certain level of instability as we modify the interpretation of the underlying matrix. We evaluate imputation strategies that provide improved prediction performance by reaching geographically smooth eigenvectors. We point on possible links between distribution of votes and the phenomenon of self-organized criticality.
Statistical Analysis of Conductor Motion in LHC Superconducting Dipole Magnets
Calvi, M; Pugnat, P; Siemko, A
2004-01-01
Premature training quenches are usually caused by the transient energy release within the magnet coil as it is energised. The dominant disturbances originate in cable motion and produce observable rapid variation in voltage signals called spikes. The experimental set up and the raw data treatment to detect these phenomena are briefly recalled. The statistical properties of different features of spikes are presented like for instance the maximal amplitude, the energy, the duration and the time correlation between events. The parameterisation of the mechanical activity of magnets is addressed. The mechanical activity of full-scale prototype and first preseries LHC dipole magnets is analysed and correlations with magnet manufacturing procedures and quench performance are established. The predictability of the quench occurrence is discussed and examples presented.
Statistical shape analysis using 3D Poisson equation--A quantitatively validated approach.
Gao, Yi; Bouix, Sylvain
2016-05-01
Statistical shape analysis has been an important area of research with applications in biology, anatomy, neuroscience, agriculture, paleontology, etc. Unfortunately, the proposed methods are rarely quantitatively evaluated, and as shown in recent studies, when they are evaluated, significant discrepancies exist in their outputs. In this work, we concentrate on the problem of finding the consistent location of deformation between two population of shapes. We propose a new shape analysis algorithm along with a framework to perform a quantitative evaluation of its performance. Specifically, the algorithm constructs a Signed Poisson Map (SPoM) by solving two Poisson equations on the volumetric shapes of arbitrary topology, and statistical analysis is then carried out on the SPoMs. The method is quantitatively evaluated on synthetic shapes and applied on real shape data sets in brain structures. Copyright © 2016 Elsevier B.V. All rights reserved.
Visual and statistical analysis of {sup 18}F-FDG PET in primary progressive aphasia
Energy Technology Data Exchange (ETDEWEB)
Matias-Guiu, Jordi A.; Moreno-Ramos, Teresa; Garcia-Ramos, Rocio; Fernandez-Matarrubia, Marta; Oreja-Guevara, Celia; Matias-Guiu, Jorge [Hospital Clinico San Carlos, Department of Neurology, Madrid (Spain); Cabrera-Martin, Maria Nieves; Perez-Castejon, Maria Jesus; Rodriguez-Rey, Cristina; Ortega-Candil, Aida; Carreras, Jose Luis [San Carlos Health Research Institute (IdISSC) Complutense University of Madrid, Department of Nuclear Medicine, Hospital Clinico San Carlos, Madrid (Spain)
2015-05-01
Diagnosing progressive primary aphasia (PPA) and its variants is of great clinical importance, and fluorodeoxyglucose (FDG) positron emission tomography (PET) may be a useful diagnostic technique. The purpose of this study was to evaluate interobserver variability in the interpretation of FDG PET images in PPA as well as the diagnostic sensitivity and specificity of the technique. We also aimed to compare visual and statistical analyses of these images. There were 10 raters who analysed 44 FDG PET scans from 33 PPA patients and 11 controls. Five raters analysed the images visually, while the other five used maps created using Statistical Parametric Mapping software. Two spatial normalization procedures were performed: global mean normalization and cerebellar normalization. Clinical diagnosis was considered the gold standard. Inter-rater concordance was moderate for visual analysis (Fleiss' kappa 0.568) and substantial for statistical analysis (kappa 0.756-0.881). Agreement was good for all three variants of PPA except for the nonfluent/agrammatic variant studied with visual analysis. The sensitivity and specificity of each rater's diagnosis of PPA was high, averaging 87.8 and 89.9 % for visual analysis and 96.9 and 90.9 % for statistical analysis using global mean normalization, respectively. In cerebellar normalization, sensitivity was 88.9 % and specificity 100 %. FDG PET demonstrated high diagnostic accuracy for the diagnosis of PPA and its variants. Inter-rater concordance was higher for statistical analysis, especially for the nonfluent/agrammatic variant. These data support the use of FDG PET to evaluate patients with PPA and show that statistical analysis methods are particularly useful for identifying the nonfluent/agrammatic variant of PPA. (orig.)
Visual and statistical analysis of 18F-FDG PET in primary progressive aphasia
International Nuclear Information System (INIS)
Matias-Guiu, Jordi A.; Moreno-Ramos, Teresa; Garcia-Ramos, Rocio; Fernandez-Matarrubia, Marta; Oreja-Guevara, Celia; Matias-Guiu, Jorge; Cabrera-Martin, Maria Nieves; Perez-Castejon, Maria Jesus; Rodriguez-Rey, Cristina; Ortega-Candil, Aida; Carreras, Jose Luis
2015-01-01
Diagnosing progressive primary aphasia (PPA) and its variants is of great clinical importance, and fluorodeoxyglucose (FDG) positron emission tomography (PET) may be a useful diagnostic technique. The purpose of this study was to evaluate interobserver variability in the interpretation of FDG PET images in PPA as well as the diagnostic sensitivity and specificity of the technique. We also aimed to compare visual and statistical analyses of these images. There were 10 raters who analysed 44 FDG PET scans from 33 PPA patients and 11 controls. Five raters analysed the images visually, while the other five used maps created using Statistical Parametric Mapping software. Two spatial normalization procedures were performed: global mean normalization and cerebellar normalization. Clinical diagnosis was considered the gold standard. Inter-rater concordance was moderate for visual analysis (Fleiss' kappa 0.568) and substantial for statistical analysis (kappa 0.756-0.881). Agreement was good for all three variants of PPA except for the nonfluent/agrammatic variant studied with visual analysis. The sensitivity and specificity of each rater's diagnosis of PPA was high, averaging 87.8 and 89.9 % for visual analysis and 96.9 and 90.9 % for statistical analysis using global mean normalization, respectively. In cerebellar normalization, sensitivity was 88.9 % and specificity 100 %. FDG PET demonstrated high diagnostic accuracy for the diagnosis of PPA and its variants. Inter-rater concordance was higher for statistical analysis, especially for the nonfluent/agrammatic variant. These data support the use of FDG PET to evaluate patients with PPA and show that statistical analysis methods are particularly useful for identifying the nonfluent/agrammatic variant of PPA. (orig.)
Detecting fire in video stream using statistical analysis
Directory of Open Access Journals (Sweden)
Koplík Karel
2017-01-01
Full Text Available The real time fire detection in video stream is one of the most interesting problems in computer vision. In fact, in most cases it would be nice to have fire detection algorithm implemented in usual industrial cameras and/or to have possibility to replace standard industrial cameras with one implementing the fire detection algorithm. In this paper, we present new algorithm for detecting fire in video. The algorithm is based on tracking suspicious regions in time with statistical analysis of their trajectory. False alarms are minimized by combining multiple detection criteria: pixel brightness, trajectories of suspicious regions for evaluating characteristic fire flickering and persistence of alarm state in sequence of frames. The resulting implementation is fast and therefore can run on wide range of affordable hardware.
Statistical mechanical analysis of LMFBR fuel cladding tubes
International Nuclear Information System (INIS)
Poncelet, J.-P.; Pay, A.
1977-01-01
The most important design requirement on fuel pin cladding for LMFBR's is its mechanical integrity. Disruptive factors include internal pressure from mixed oxide fuel fission gas release, thermal stresses and high temperature creep, neutron-induced differential void-swelling as a source of stress in the cladding and irradiation creep of stainless steel material, corrosion by fission products. Under irradiation these load-restraining mechanisms are accentuated by stainless steel embrittlement and strength alterations. To account for the numerous uncertainties involved in the analysis by theoretical models and computer codes statistical tools are unavoidably requested, i.e. Monte Carlo simulation methods. Thanks to these techniques, uncertainties in nominal characteristics, material properties and environmental conditions can be linked up in a correct way and used for a more accurate conceptual design. (Auth.)
Langmuir waveforms at interplanetary shocks: STEREO statistical analysis
Briand, C.
2016-12-01
Wave-particle interactions and particle acceleration are the two main processes allowing energy dissipation at non collisional shocks. Ion acceleration has been deeply studied for many years, also for their central role in the shock front reformation. Electron dynamics is also important in the shock dynamics through the instabilities they can generate which may impact the ion dynamics.Particle measurements can be efficiently completed by wave measurements to determine the characteristics of the electron beams and study the turbulence of the medium. Electric waveforms obtained from the S/WAVES instrument of the STEREO mission between 2007 to 2014 are analyzed. Thus, clear signature of Langmuir waves are observed on 41 interplanetary shocks. These data enable a statistical analysis and to deduce some characteristics of the electron dynamics on different shocks sources (SIR or ICME) and types (quasi-perpendicular or quasi-parallel). The conversion process between electrostatic to electromagnetic waves has also been tested in several cases.
Analysis of Official Suicide Statistics in Spain (1910-2011
Directory of Open Access Journals (Sweden)
2017-01-01
Full Text Available In this article we examine the evolution of suicide rates in Spain from 1910 to 2011. As something new, we use standardised suicide rates, making them perfectly comparable geographically and in time, as they no longer reflect population structure. Using historical data from a series of socioeconomic variables for all Spain's provinces and applying new techniques for the statistical analysis of panel data, we are able to confirm many of the hypotheses established by Durkheim at the end of the 19th century, especially those related to fertility and marriage rates, age, sex and the aging index. Our findings, however, contradict Durkheim's approach regarding the impact of urbanisation processes and poverty on suicide.
Higher order statistical moment application for solar PV potential analysis
Basri, Mohd Juhari Mat; Abdullah, Samizee; Azrulhisham, Engku Ahmad; Harun, Khairulezuan
2016-10-01
Solar photovoltaic energy could be as alternative energy to fossil fuel, which is depleting and posing a global warming problem. However, this renewable energy is so variable and intermittent to be relied on. Therefore the knowledge of energy potential is very important for any site to build this solar photovoltaic power generation system. Here, the application of higher order statistical moment model is being analyzed using data collected from 5MW grid-connected photovoltaic system. Due to the dynamic changes of skewness and kurtosis of AC power and solar irradiance distributions of the solar farm, Pearson system where the probability distribution is calculated by matching their theoretical moments with that of the empirical moments of a distribution could be suitable for this purpose. On the advantage of the Pearson system in MATLAB, a software programming has been developed to help in data processing for distribution fitting and potential analysis for future projection of amount of AC power and solar irradiance availability.
Statistical uncertainty analysis of radon transport in nonisothermal, unsaturated soils
International Nuclear Information System (INIS)
Holford, D.J.; Owczarski, P.C.; Gee, G.W.; Freeman, H.D.
1990-10-01
To accurately predict radon fluxes soils to the atmosphere, we must know more than the radium content of the soil. Radon flux from soil is affected not only by soil properties, but also by meteorological factors such as air pressure and temperature changes at the soil surface, as well as the infiltration of rainwater. Natural variations in meteorological factors and soil properties contribute to uncertainty in subsurface model predictions of radon flux, which, when coupled with a building transport model, will also add uncertainty to predictions of radon concentrations in homes. A statistical uncertainty analysis using our Rn3D finite-element numerical model was conducted to assess the relative importance of these meteorological factors and the soil properties affecting radon transport. 10 refs., 10 figs., 3 tabs
Performance analysis of opportunistic nonregenerative relaying
Tourki, Kamel; Alouini, Mohamed-Slim; Qaraqe, Khalid A.; Yang, Hongchuan
2013-01-01
Opportunistic relaying in cooperative communication depends on careful relay selection. However, the traditional centralized method used for opportunistic amplify-and-forward protocols requires precise measurements of channel state information at the destination. In this paper, we adopt the max-min criterion as a relay selection framework for opportunistic amplify-and-forward cooperative communications, which was exhaustively used for the decode-and-forward protocol, and offer an accurate performance analysis based on exact statistics of the local signal-to-noise ratios of the best relay. Furthermore, we evaluate the asymptotical performance and deduce the diversity order of our proposed scheme. Finally, we validate our analysis by showing that performance simulation results coincide with our analytical results over Rayleigh fading channels, and we compare the max-min relay selection with their centralized channel state information-based and partial relay selection counterparts.
On the analysis of line profile variations: A statistical approach
International Nuclear Information System (INIS)
McCandliss, S.R.
1988-01-01
This study is concerned with the empirical characterization of the line profile variations (LPV), which occur in many of and Wolf-Rayet stars. The goal of the analysis is to gain insight into the physical mechanisms producing the variations. The analytic approach uses a statistical method to quantify the significance of the LPV and to identify those regions in the line profile which are undergoing statistically significant variations. Line positions and flux variations are then measured and subject to temporal and correlative analysis. Previous studies of LPV have for the most part been restricted to observations of a single line. Important information concerning the range and amplitude of the physical mechanisms involved can be obtained by simultaneously observing spectral features formed over a range of depths in the extended mass losing atmospheres of massive, luminous stars. Time series of a Wolf-Rayet and two of stars with nearly complete spectral coverage from 3940 angstrom to 6610 angstrom and with spectral resolution of R = 10,000 are analyzed here. These three stars exhibit a wide range of both spectral and temporal line profile variations. The HeII Pickering lines of HD 191765 show a monotonic increase in the peak rms variation amplitude with lines formed at progressively larger radii in the Wolf-Rayet star wind. Two times scales of variation have been identified in this star: a less than one day variation associated with small scale flickering in the peaks of the line profiles and a greater than one day variation associated with large scale asymmetric changes in the overall line profile shapes. However, no convincing period phenomena are evident at those periods which are well sampled in this time series
A STATISTICAL ANALYSIS OF LARYNGEAL MALIGNANCIES AT OUR INSTITUTION
Directory of Open Access Journals (Sweden)
Bharathi Mohan Mathan
2017-03-01
Full Text Available BACKGROUND Malignancies of larynx are an increasing global burden with a distribution of approximately 2-5% of all malignancies with an incidence of 3.6/1,00,000 for men and 1.3/1,00,000 for women with a male-to-female ratio of 4:1. Smoking and alcohol are major established risk factors. More than 90-95% of all malignancies are squamous cell type. Three main subsite of laryngeal malignancies are glottis, supraglottis and subglottis. Improved surgical techniques and advanced chemoradiotherapy has increased the overall 5 year survival rate. The above study is statistical analysis of laryngeal malignancies at our institution for a period of one year and analysis of pattern of distribution, aetiology, sites and subsites and causes for recurrence. MATERIALS AND METHODS Based on the statistical data available in the institution for the period of one year from January 2016-December 2016, all laryngeal malignancies were analysed with respect to demographic pattern, age, gender, site, subsite, aetiology, staging, treatment received and probable cause for failure of treatment. Patients were followed up for 12 months period during the study. RESULTS Total number of cases studied are 27 (twenty seven. Male cases are 23 and female cases are 4, male-to-female ratio is 5.7:1, most common age is above 60 years, most common site is supraglottis, most common type is moderately-differentiated squamous cell carcinoma, most common cause for relapse or recurrence is advanced stage of disease and poor differentiation. CONCLUSION The commonest age occurrence at the end of the study is above 60 years and male-to-female ratio is 5.7:1, which is slightly above the international standards. Most common site is supraglottis and not glottis. The relapse and recurrences are higher compared to the international standards.
Spectral signature verification using statistical analysis and text mining
DeCoster, Mallory E.; Firpi, Alexe H.; Jacobs, Samantha K.; Cone, Shelli R.; Tzeng, Nigel H.; Rodriguez, Benjamin M.
2016-05-01
In the spectral science community, numerous spectral signatures are stored in databases representative of many sample materials collected from a variety of spectrometers and spectroscopists. Due to the variety and variability of the spectra that comprise many spectral databases, it is necessary to establish a metric for validating the quality of spectral signatures. This has been an area of great discussion and debate in the spectral science community. This paper discusses a method that independently validates two different aspects of a spectral signature to arrive at a final qualitative assessment; the textual meta-data and numerical spectral data. Results associated with the spectral data stored in the Signature Database1 (SigDB) are proposed. The numerical data comprising a sample material's spectrum is validated based on statistical properties derived from an ideal population set. The quality of the test spectrum is ranked based on a spectral angle mapper (SAM) comparison to the mean spectrum derived from the population set. Additionally, the contextual data of a test spectrum is qualitatively analyzed using lexical analysis text mining. This technique analyzes to understand the syntax of the meta-data to provide local learning patterns and trends within the spectral data, indicative of the test spectrum's quality. Text mining applications have successfully been implemented for security2 (text encryption/decryption), biomedical3 , and marketing4 applications. The text mining lexical analysis algorithm is trained on the meta-data patterns of a subset of high and low quality spectra, in order to have a model to apply to the entire SigDB data set. The statistical and textual methods combine to assess the quality of a test spectrum existing in a database without the need of an expert user. This method has been compared to other validation methods accepted by the spectral science community, and has provided promising results when a baseline spectral signature is
Wavelet Statistical Analysis of Low-Latitude Geomagnetic Measurements
Papa, A. R.; Akel, A. F.
2009-05-01
Following previous works by our group (Papa et al., JASTP, 2006), where we analyzed a series of records acquired at the Vassouras National Geomagnetic Observatory in Brazil for the month of October 2000, we introduced a wavelet analysis for the same type of data and for other periods. It is well known that wavelets allow a more detailed study in several senses: the time window for analysis can be drastically reduced if compared to other traditional methods (Fourier, for example) and at the same time allow an almost continuous accompaniment of both amplitude and frequency of signals as time goes by. This advantage brings some possibilities for potentially useful forecasting methods of the type also advanced by our group in previous works (see for example, Papa and Sosman, JASTP, 2008). However, the simultaneous statistical analysis of both time series (in our case amplitude and frequency) is a challenging matter and is in this sense that we have found what we consider our main goal. Some possible trends for future works are advanced.
Li, Gaoming; Yi, Dali; Wu, Xiaojiao; Liu, Xiaoyu; Zhang, Yanqi; Liu, Ling; Yi, Dong
2015-01-01
Background Although a substantial number of studies focus on the teaching and application of medical statistics in China, few studies comprehensively evaluate the recognition of and demand for medical statistics. In addition, the results of these various studies differ and are insufficiently comprehensive and systematic. Objectives This investigation aimed to evaluate the general cognition of and demand for medical statistics by undergraduates, graduates, and medical staff in China. Methods We performed a comprehensive database search related to the cognition of and demand for medical statistics from January 2007 to July 2014 and conducted a meta-analysis of non-controlled studies with sub-group analysis for undergraduates, graduates, and medical staff. Results There are substantial differences with respect to the cognition of theory in medical statistics among undergraduates (73.5%), graduates (60.7%), and medical staff (39.6%). The demand for theory in medical statistics is high among graduates (94.6%), undergraduates (86.1%), and medical staff (88.3%). Regarding specific statistical methods, the cognition of basic statistical methods is higher than of advanced statistical methods. The demand for certain advanced statistical methods, including (but not limited to) multiple analysis of variance (ANOVA), multiple linear regression, and logistic regression, is higher than that for basic statistical methods. The use rates of the Statistical Package for the Social Sciences (SPSS) software and statistical analysis software (SAS) are only 55% and 15%, respectively. Conclusion The overall statistical competence of undergraduates, graduates, and medical staff is insufficient, and their ability to practically apply their statistical knowledge is limited, which constitutes an unsatisfactory state of affairs for medical statistics education. Because the demand for skills in this area is increasing, the need to reform medical statistics education in China has become urgent
Study on statistical analysis of nonlinear and nonstationary reactor noises
International Nuclear Information System (INIS)
Hayashi, Koji
1993-03-01
For the purpose of identification of nonlinear mechanism and diagnosis of nuclear reactor systems, analysis methods for nonlinear reactor noise have been studied. By adding newly developed approximate response function to GMDH, a conventional nonlinear identification method, a useful method for nonlinear spectral analysis and identification of nonlinear mechanism has been established. Measurement experiment and analysis were performed on the reactor power oscillation observed in the NSRR installed at the JAERI and the cause of the instability was clarified. Furthermore, the analysis and data recording methods for nonstationary noise have been studied. By improving the time resolution of instantaneous autoregressive spectrum, a method for monitoring and diagnosis of operational status of nuclear reactor has been established. A preprocessing system for recording of nonstationary reactor noise was developed and its usability was demonstrated through a measurement experiment. (author) 139 refs
International Nuclear Information System (INIS)
Létourneau, Daniel; McNiven, Andrea; Keller, Harald; Wang, An; Amin, Md Nurul; Pearce, Jim; Norrlinger, Bernhard; Jaffray, David A.
2014-01-01
Purpose: High-quality radiation therapy using highly conformal dose distributions and image-guided techniques requires optimum machine delivery performance. In this work, a monitoring system for multileaf collimator (MLC) performance, integrating semiautomated MLC quality control (QC) tests and statistical process control tools, was developed. The MLC performance monitoring system was used for almost a year on two commercially available MLC models. Control charts were used to establish MLC performance and assess test frequency required to achieve a given level of performance. MLC-related interlocks and servicing events were recorded during the monitoring period and were investigated as indicators of MLC performance variations. Methods: The QC test developed as part of the MLC performance monitoring system uses 2D megavoltage images (acquired using an electronic portal imaging device) of 23 fields to determine the location of the leaves with respect to the radiation isocenter. The precision of the MLC performance monitoring QC test and the MLC itself was assessed by detecting the MLC leaf positions on 127 megavoltage images of a static field. After initial calibration, the MLC performance monitoring QC test was performed 3–4 times/week over a period of 10–11 months to monitor positional accuracy of individual leaves for two different MLC models. Analysis of test results was performed using individuals control charts per leaf with control limits computed based on the measurements as well as two sets of specifications of ±0.5 and ±1 mm. Out-of-specification and out-of-control leaves were automatically flagged by the monitoring system and reviewed monthly by physicists. MLC-related interlocks reported by the linear accelerator and servicing events were recorded to help identify potential causes of nonrandom MLC leaf positioning variations. Results: The precision of the MLC performance monitoring QC test and the MLC itself was within ±0.22 mm for most MLC leaves
Létourneau, Daniel; Wang, An; Amin, Md Nurul; Pearce, Jim; McNiven, Andrea; Keller, Harald; Norrlinger, Bernhard; Jaffray, David A
2014-12-01
High-quality radiation therapy using highly conformal dose distributions and image-guided techniques requires optimum machine delivery performance. In this work, a monitoring system for multileaf collimator (MLC) performance, integrating semiautomated MLC quality control (QC) tests and statistical process control tools, was developed. The MLC performance monitoring system was used for almost a year on two commercially available MLC models. Control charts were used to establish MLC performance and assess test frequency required to achieve a given level of performance. MLC-related interlocks and servicing events were recorded during the monitoring period and were investigated as indicators of MLC performance variations. The QC test developed as part of the MLC performance monitoring system uses 2D megavoltage images (acquired using an electronic portal imaging device) of 23 fields to determine the location of the leaves with respect to the radiation isocenter. The precision of the MLC performance monitoring QC test and the MLC itself was assessed by detecting the MLC leaf positions on 127 megavoltage images of a static field. After initial calibration, the MLC performance monitoring QC test was performed 3-4 times/week over a period of 10-11 months to monitor positional accuracy of individual leaves for two different MLC models. Analysis of test results was performed using individuals control charts per leaf with control limits computed based on the measurements as well as two sets of specifications of ± 0.5 and ± 1 mm. Out-of-specification and out-of-control leaves were automatically flagged by the monitoring system and reviewed monthly by physicists. MLC-related interlocks reported by the linear accelerator and servicing events were recorded to help identify potential causes of nonrandom MLC leaf positioning variations. The precision of the MLC performance monitoring QC test and the MLC itself was within ± 0.22 mm for most MLC leaves and the majority of the
International Nuclear Information System (INIS)
Molchan, G.M.; Kronrod, T.L.; Dmitrieva, O.E.
1995-03-01
The catalog of earthquakes of Italy (1900-1993) is analyzed in the present work. The following problems have been considered: 1) a choice of the operating magnitude, 2) an analysis of data completeness, and 3) a grouping (in time and in space). The catalog has been separated into main shocks and aftershocks. Statistical estimations of seismicity parameters (a,b) are performed for the seismogenetic zones defined by GNDT. The non-standard elements of the analysis performed are: (a) statistical estimation and comparison of seismicity parameters under the condition of arbitrary data grouping in magnitude, time and space; (b) use of a not conventional statistical method for the aftershock identification; the method is based on the idea of optimizing two kinds of errors in the aftershock identification process; (c) use of the aftershock zones to reveal seismically- interrelated seismogenic zones. This procedure contributes to the stability of the estimation of the ''b-value'' Refs, 25 figs, tabs
Parametric analysis of the statistical model of the stick-slip process
Lima, Roberta; Sampaio, Rubens
2017-06-01
In this paper it is performed a parametric analysis of the statistical model of the response of a dry-friction oscillator. The oscillator is a spring-mass system which moves over a base with a rough surface. Due to this roughness, the mass is subject to a dry-frictional force modeled as a Coulomb friction. The system is stochastically excited by an imposed bang-bang base motion. The base velocity is modeled by a Poisson process for which a probabilistic model is fully specified. The excitation induces in the system stochastic stick-slip oscillations. The system response is composed by a random sequence alternating stick and slip-modes. With realizations of the system, a statistical model is constructed for this sequence. In this statistical model, the variables of interest of the sequence are modeled as random variables, as for example, the number of time intervals in which stick or slip occur, the instants at which they begin, and their duration. Samples of the system response are computed by integration of the dynamic equation of the system using independent samples of the base motion. Statistics and histograms of the random variables which characterize the stick-slip process are estimated for the generated samples. The objective of the paper is to analyze how these estimated statistics and histograms vary with the system parameters, i.e., to make a parametric analysis of the statistical model of the stick-slip process.
Wang, Mingyu; Han, Lijuan; Liu, Shasha; Zhao, Xuebing; Yang, Jinghua; Loh, Soh Kheang; Sun, Xiaomin; Zhang, Chenxi; Fang, Xu
2015-09-01
Renewable energy from lignocellulosic biomass has been deemed an alternative to depleting fossil fuels. In order to improve this technology, we aim to develop robust mathematical models for the enzymatic lignocellulose degradation process. By analyzing 96 groups of previously published and newly obtained lignocellulose saccharification results and fitting them to Weibull distribution, we discovered Weibull statistics can accurately predict lignocellulose saccharification data, regardless of the type of substrates, enzymes and saccharification conditions. A mathematical model for enzymatic lignocellulose degradation was subsequently constructed based on Weibull statistics. Further analysis of the mathematical structure of the model and experimental saccharification data showed the significance of the two parameters in this model. In particular, the λ value, defined the characteristic time, represents the overall performance of the saccharification system. This suggestion was further supported by statistical analysis of experimental saccharification data and analysis of the glucose production levels when λ and n values change. In conclusion, the constructed Weibull statistics-based model can accurately predict lignocellulose hydrolysis behavior and we can use the λ parameter to assess the overall performance of enzymatic lignocellulose degradation. Advantages and potential applications of the model and the λ value in saccharification performance assessment were discussed. Copyright © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
A Statistic Analysis Of Romanian Seaside Hydro Tourism
Secara Mirela
2011-01-01
Tourism represents one of the ways of spending spare time for rest, recreation, treatment and entertainment, and the specific aspect of Constanta County economy is touristic and spa capitalization of Romanian seaside. In order to analyze hydro tourism on Romanian seaside we have used statistic indicators within tourism as well as statistic methods such as chronological series, interdependent statistic series, regression and statistic correlation. The major objective of this research is to rai...
TACO: fuel pin performance analysis
International Nuclear Information System (INIS)
Stoudt, R.H.; Buchanan, D.T.; Buescher, B.J.; Losh, L.L.; Wilson, H.W.; Henningson, P.J.
1977-08-01
The thermal performance of fuel in an LWR during its operational lifetime must be described for LOCA analysis as well as for other safety analyses. The determination of stored energy in the LOCA analysis, for example, requires a conservative fuel pin thermal performance model that is capable of calculating fuel and cladding behavior, including the gap conductance between the fuel and cladding, as a function of burnup. The determination of parameters that affect the fuel and cladding performance, such as fuel densification, fission gas release, cladding dimensional changes, fuel relocation, and thermal expansion, should be accounted for in the model. Babcock and Wilcox (B and W) has submitted a topical report, BAW-10087P, December 1975, which describes their thermal performance model TACO. A summary of the elements that comprise the TACO model and an evaluation are presented
Tucker tensor analysis of Matern functions in spatial statistics
Litvinenko, Alexander
2018-04-20
Low-rank Tucker tensor methods in spatial statistics 1. Motivation: improve statistical models 2. Motivation: disadvantages of matrices 3. Tools: Tucker tensor format 4. Tensor approximation of Matern covariance function via FFT 5. Typical statistical operations in Tucker tensor format 6. Numerical experiments
Three-Dimensional Assembly Tolerance Analysis Based on the Jacobian-Torsor Statistical Model
Directory of Open Access Journals (Sweden)
Peng Heping
2017-01-01
Full Text Available The unified Jacobian-Torsor model has been developed for deterministic (worst case tolerance analysis. This paper presents a comprehensive model for performing statistical tolerance analysis by integrating the unified Jacobian-Torsor model and Monte Carlo simulation. In this model, an assembly is sub-divided into surfaces, the Small Displacements Torsor (SDT parameters are used to express the relative position between any two surfaces of the assembly. Then, 3D dimension-chain can be created by using a surface graph of the assembly and the unified Jacobian-Torsor model is developed based on the effect of each functional element on the whole functional requirements of products. Finally, Monte Carlo simulation is implemented for the statistical tolerance analysis. A numerical example is given to demonstrate the capability of the proposed method in handling three-dimensional assembly tolerance analysis.
Statistical mechanical analysis of the linear vector channel in digital communication
International Nuclear Information System (INIS)
Takeda, Koujin; Hatabu, Atsushi; Kabashima, Yoshiyuki
2007-01-01
A statistical mechanical framework to analyze linear vector channel models in digital wireless communication is proposed for a large system. The framework is a generalization of that proposed for code-division multiple-access systems in Takeda et al (2006 Europhys. Lett. 76 1193) and enables the analysis of the system in which the elements of the channel transfer matrix are statistically correlated with each other. The significance of the proposed scheme is demonstrated by assessing the performance of an existing model of multi-input multi-output communication systems
Statistical analysis of CCSN/SS7 traffic data from working CCS subnetworks
Duffy, Diane E.; McIntosh, Allen A.; Rosenstein, Mark; Willinger, Walter
1994-04-01
In this paper, we report on an ongoing statistical analysis of actual CCSN traffic data. The data consist of approximately 170 million signaling messages collected from a variety of different working CCS subnetworks. The key findings from our analysis concern: (1) the characteristics of both the telephone call arrival process and the signaling message arrival process; (2) the tail behavior of the call holding time distribution; and (3) the observed performance of the CCSN with respect to a variety of performance and reliability measurements.
Global health business: the production and performativity of statistics in Sierra Leone and Germany.
Erikson, Susan L
2012-01-01
The global push for health statistics and electronic digital health information systems is about more than tracking health incidence and prevalence. It is also experienced on the ground as means to develop and maintain particular norms of health business, knowledge, and decision- and profit-making that are not innocent. Statistics make possible audit and accountability logics that undergird the management of health at a distance and that are increasingly necessary to the business of health. Health statistics are inextricable from their social milieus, yet as business artifacts they operate as if they are freely formed, objectively originated, and accurate. This article explicates health statistics as cultural forms and shows how they have been produced and performed in two very different countries: Sierra Leone and Germany. In both familiar and surprising ways, this article shows how statistics and their pursuit organize and discipline human behavior, constitute subject positions, and reify existing relations of power.
Business Statistics: A Comparison of Student Performance in Three Learning Modes
Simmons, Gerald R.
2014-01-01
The purpose of this study was to compare the performance of three teaching modes and age groups of business statistics sections in terms of course exam scores. The research questions were formulated to determine the performance of the students within each teaching mode, to compare each mode in terms of exam scores, and to compare exam scores by…
Oliveira Mendes, Thiago de; Pinto, Liliane Pereira; Santos, Laurita dos; Tippavajhala, Vamshi Krishna; Téllez Soto, Claudio Alberto; Martin, Airton Abrahão
2016-07-01
The analysis of biological systems by spectroscopic techniques involves the evaluation of hundreds to thousands of variables. Hence, different statistical approaches are used to elucidate regions that discriminate classes of samples and to propose new vibrational markers for explaining various phenomena like disease monitoring, mechanisms of action of drugs, food, and so on. However, the technical statistics are not always widely discussed in applied sciences. In this context, this work presents a detailed discussion including the various steps necessary for proper statistical analysis. It includes univariate parametric and nonparametric tests, as well as multivariate unsupervised and supervised approaches. The main objective of this study is to promote proper understanding of the application of various statistical tools in these spectroscopic methods used for the analysis of biological samples. The discussion of these methods is performed on a set of in vivo confocal Raman spectra of human skin analysis that aims to identify skin aging markers. In the Appendix, a complete routine of data analysis is executed in a free software that can be used by the scientific community involved in these studies.
Institute of Scientific and Technical Information of China (English)
俞敏
2013-01-01
通过对3G性能统计的研究，制定了网络短板快速查询的方法和提供给业务部门话务、流量分析查询的手段，并结合具体案例，提出网络短板的解决手段。经过性能统计分析，可快速找出网络问题，并及时提供给业务部门所需要的话务及流量信息，充分体现网络为市场服务的宗旨。%Based on the statistics analysis of 3G performance, fast query methods for network short board are proposed in this paper, and query manners for telephone traffic flow analysis are provided to operating department, and the solution for short board is given through a specific case. The proposed strategy could find the problems of network quickly through the statistics analysis of 3G performance, and meanwhile could provide traffic flow information to the business department in time, which fully embodies that networks serve the market as purpose.
Predicting Smoking Status Using Machine Learning Algorithms and Statistical Analysis
Directory of Open Access Journals (Sweden)
Charles Frank
2018-03-01
Full Text Available Smoking has been proven to negatively affect health in a multitude of ways. As of 2009, smoking has been considered the leading cause of preventable morbidity and mortality in the United States, continuing to plague the country’s overall health. This study aims to investigate the viability and effectiveness of some machine learning algorithms for predicting the smoking status of patients based on their blood tests and vital readings results. The analysis of this study is divided into two parts: In part 1, we use One-way ANOVA analysis with SAS tool to show the statistically significant difference in blood test readings between smokers and non-smokers. The results show that the difference in INR, which measures the effectiveness of anticoagulants, was significant in favor of non-smokers which further confirms the health risks associated with smoking. In part 2, we use five machine learning algorithms: Naïve Bayes, MLP, Logistic regression classifier, J48 and Decision Table to predict the smoking status of patients. To compare the effectiveness of these algorithms we use: Precision, Recall, F-measure and Accuracy measures. The results show that the Logistic algorithm outperformed the four other algorithms with Precision, Recall, F-Measure, and Accuracy of 83%, 83.4%, 83.2%, 83.44%, respectively.
Criminal victimization in Ukraine: analysis of statistical data
Directory of Open Access Journals (Sweden)
Serhiy Nezhurbida
2007-12-01
Full Text Available The article is based on the analysis of statistical data provided by law-enforcement, judicial and other bodies of Ukraine. The given analysis allows us to give an accurate quantity of a current status of crime victimization in Ukraine, to characterize its basic features (level, rate, structure, dynamics, and etc.. L’article se concentre sur l’analyse des données statystiques fournies par les institutions de contrôle sociale (forces de police et magistrature et par d’autres organes institutionnels ukrainiens. Les analyses effectuées attirent l'attention sur la situation actuelle des victimes du crime en Ukraine et aident à délinéer leur principales caractéristiques (niveau, taux, structure, dynamiques, etc.L’articolo si basa sull’analisi dei dati statistici forniti dalle agenzie del controllo sociale (forze dell'ordine e magistratura e da altri organi istituzionali ucraini. Le analisi effettuate forniscono molte informazioni sulla situazione attuale delle vittime del crimine in Ucraina e aiutano a delinearne le caratteristiche principali (livello, tasso, struttura, dinamiche, ecc..
A statistical design for testing apomictic diversification through linkage analysis.
Zeng, Yanru; Hou, Wei; Song, Shuang; Feng, Sisi; Shen, Lin; Xia, Guohua; Wu, Rongling
2014-03-01
The capacity of apomixis to generate maternal clones through seed reproduction has made it a useful characteristic for the fixation of heterosis in plant breeding. It has been observed that apomixis displays pronounced intra- and interspecific diversification, but the genetic mechanisms underlying this diversification remains elusive, obstructing the exploitation of this phenomenon in practical breeding programs. By capitalizing on molecular information in mapping populations, we describe and assess a statistical design that deploys linkage analysis to estimate and test the pattern and extent of apomictic differences at various levels from genotypes to species. The design is based on two reciprocal crosses between two individuals each chosen from a hermaphrodite or monoecious species. A multinomial distribution likelihood is constructed by combining marker information from two crosses. The EM algorithm is implemented to estimate the rate of apomixis and test its difference between two plant populations or species as the parents. The design is validated by computer simulation. A real data analysis of two reciprocal crosses between hickory (Carya cathayensis) and pecan (C. illinoensis) demonstrates the utilization and usefulness of the design in practice. The design provides a tool to address fundamental and applied questions related to the evolution and breeding of apomixis.
Metaviz: interactive statistical and visual analysis of metagenomic data.
Wagner, Justin; Chelaru, Florin; Kancherla, Jayaram; Paulson, Joseph N; Zhang, Alexander; Felix, Victor; Mahurkar, Anup; Elmqvist, Niklas; Corrada Bravo, Héctor
2018-04-06
Large studies profiling microbial communities and their association with healthy or disease phenotypes are now commonplace. Processed data from many of these studies are publicly available but significant effort is required for users to effectively organize, explore and integrate it, limiting the utility of these rich data resources. Effective integrative and interactive visual and statistical tools to analyze many metagenomic samples can greatly increase the value of these data for researchers. We present Metaviz, a tool for interactive exploratory data analysis of annotated microbiome taxonomic community profiles derived from marker gene or whole metagenome shotgun sequencing. Metaviz is uniquely designed to address the challenge of browsing the hierarchical structure of metagenomic data features while rendering visualizations of data values that are dynamically updated in response to user navigation. We use Metaviz to provide the UMD Metagenome Browser web service, allowing users to browse and explore data for more than 7000 microbiomes from published studies. Users can also deploy Metaviz as a web service, or use it to analyze data through the metavizr package to interoperate with state-of-the-art analysis tools available through Bioconductor. Metaviz is free and open source with the code, documentation and tutorials publicly accessible.
Data Analysis & Statistical Methods for Command File Errors
Meshkat, Leila; Waggoner, Bruce; Bryant, Larry
2014-01-01
This paper explains current work on modeling for managing the risk of command file errors. It is focused on analyzing actual data from a JPL spaceflight mission to build models for evaluating and predicting error rates as a function of several key variables. We constructed a rich dataset by considering the number of errors, the number of files radiated, including the number commands and blocks in each file, as well as subjective estimates of workload and operational novelty. We have assessed these data using different curve fitting and distribution fitting techniques, such as multiple regression analysis, and maximum likelihood estimation to see how much of the variability in the error rates can be explained with these. We have also used goodness of fit testing strategies and principal component analysis to further assess our data. Finally, we constructed a model of expected error rates based on the what these statistics bore out as critical drivers to the error rate. This model allows project management to evaluate the error rate against a theoretically expected rate as well as anticipate future error rates.
Recurrence time statistics: versatile tools for genomic DNA sequence analysis.
Cao, Yinhe; Tung, Wen-Wen; Gao, J B
2004-01-01
With the completion of the human and a few model organisms' genomes, and the genomes of many other organisms waiting to be sequenced, it has become increasingly important to develop faster computational tools which are capable of easily identifying the structures and extracting features from DNA sequences. One of the more important structures in a DNA sequence is repeat-related. Often they have to be masked before protein coding regions along a DNA sequence are to be identified or redundant expressed sequence tags (ESTs) are to be sequenced. Here we report a novel recurrence time based method for sequence analysis. The method can conveniently study all kinds of periodicity and exhaustively find all repeat-related features from a genomic DNA sequence. An efficient codon index is also derived from the recurrence time statistics, which has the salient features of being largely species-independent and working well on very short sequences. Efficient codon indices are key elements of successful gene finding algorithms, and are particularly useful for determining whether a suspected EST belongs to a coding or non-coding region. We illustrate the power of the method by studying the genomes of E. coli, the yeast S. cervisivae, the nematode worm C. elegans, and the human, Homo sapiens. Computationally, our method is very efficient. It allows us to carry out analysis of genomes on the whole genomic scale by a PC.
A statistical method for draft tube pressure pulsation analysis
International Nuclear Information System (INIS)
Doerfler, P K; Ruchonnet, N
2012-01-01
Draft tube pressure pulsation (DTPP) in Francis turbines is composed of various components originating from different physical phenomena. These components may be separated because they differ by their spatial relationships and by their propagation mechanism. The first step for such an analysis was to distinguish between so-called synchronous and asynchronous pulsations; only approximately periodic phenomena could be described in this manner. However, less regular pulsations are always present, and these become important when turbines have to operate in the far off-design range, in particular at very low load. The statistical method described here permits to separate the stochastic (random) component from the two traditional 'regular' components. It works in connection with the standard technique of model testing with several pressure signals measured in draft tube cone. The difference between the individual signals and the averaged pressure signal, together with the coherence between the individual pressure signals is used for analysis. An example reveals that a generalized, non-periodic version of the asynchronous pulsation is important at low load.
Anomalous heat transfer modes of nanofluids: a review based on statistical analysis
2011-01-01
This paper contains the results of a concise statistical review analysis of a large amount of publications regarding the anomalous heat transfer modes of nanofluids. The application of nanofluids as coolants is a novel practise with no established physical foundations explaining the observed anomalous heat transfer. As a consequence, traditional methods of performing a literature review may not be adequate in presenting objectively the results representing the bulk of the available literature. The current literature review analysis aims to resolve the problems faced by researchers in the past by employing an unbiased statistical analysis to present and reveal the current trends and general belief of the scientific community regarding the anomalous heat transfer modes of nanofluids. The thermal performance analysis indicated that statistically there exists a variable enhancement for conduction, convection/mixed heat transfer, pool boiling heat transfer and critical heat flux modes. The most popular proposed mechanisms in the literature to explain heat transfer in nanofluids are revealed, as well as possible trends between nanofluid properties and thermal performance. The review also suggests future experimentation to provide more conclusive answers to the control mechanisms and influential parameters of heat transfer in nanofluids. PMID:21711932
Anomalous heat transfer modes of nanofluids: a review based on statistical analysis
Sergis, Antonis; Hardalupas, Yannis
2011-05-01
This paper contains the results of a concise statistical review analysis of a large amount of publications regarding the anomalous heat transfer modes of nanofluids. The application of nanofluids as coolants is a novel practise with no established physical foundations explaining the observed anomalous heat transfer. As a consequence, traditional methods of performing a literature review may not be adequate in presenting objectively the results representing the bulk of the available literature. The current literature review analysis aims to resolve the problems faced by researchers in the past by employing an unbiased statistical analysis to present and reveal the current trends and general belief of the scientific community regarding the anomalous heat transfer modes of nanofluids. The thermal performance analysis indicated that statistically there exists a variable enhancement for conduction, convection/mixed heat transfer, pool boiling heat transfer and critical heat flux modes. The most popular proposed mechanisms in the literature to explain heat transfer in nanofluids are revealed, as well as possible trends between nanofluid properties and thermal performance. The review also suggests future experimentation to provide more conclusive answers to the control mechanisms and influential parameters of heat transfer in nanofluids.
Anomalous heat transfer modes of nanofluids: a review based on statistical analysis
Directory of Open Access Journals (Sweden)
Sergis Antonis
2011-01-01
Full Text Available Abstract This paper contains the results of a concise statistical review analysis of a large amount of publications regarding the anomalous heat transfer modes of nanofluids. The application of nanofluids as coolants is a novel practise with no established physical foundations explaining the observed anomalous heat transfer. As a consequence, traditional methods of performing a literature review may not be adequate in presenting objectively the results representing the bulk of the available literature. The current literature review analysis aims to resolve the problems faced by researchers in the past by employing an unbiased statistical analysis to present and reveal the current trends and general belief of the scientific community regarding the anomalous heat transfer modes of nanofluids. The thermal performance analysis indicated that statistically there exists a variable enhancement for conduction, convection/mixed heat transfer, pool boiling heat transfer and critical heat flux modes. The most popular proposed mechanisms in the literature to explain heat transfer in nanofluids are revealed, as well as possible trends between nanofluid properties and thermal performance. The review also suggests future experimentation to provide more conclusive answers to the control mechanisms and influential parameters of heat transfer in nanofluids.
Hendikawati, P.; Arifudin, R.; Zahid, M. Z.
2018-03-01
This study aims to design an android Statistics Data Analysis application that can be accessed through mobile devices to making it easier for users to access. The Statistics Data Analysis application includes various topics of basic statistical along with a parametric statistics data analysis application. The output of this application system is parametric statistics data analysis that can be used for students, lecturers, and users who need the results of statistical calculations quickly and easily understood. Android application development is created using Java programming language. The server programming language uses PHP with the Code Igniter framework, and the database used MySQL. The system development methodology used is the Waterfall methodology with the stages of analysis, design, coding, testing, and implementation and system maintenance. This statistical data analysis application is expected to support statistical lecturing activities and make students easier to understand the statistical analysis of mobile devices.
Statistical analysis of cone penetration resistance of railway ballast
Directory of Open Access Journals (Sweden)
Saussine Gilles
2017-01-01
Full Text Available Dynamic penetrometer tests are widely used in geotechnical studies for soils characterization but their implementation tends to be difficult. The light penetrometer test is able to give information about a cone resistance useful in the field of geotechnics and recently validated as a parameter for the case of coarse granular materials. In order to characterize directly the railway ballast on track and sublayers of ballast, a huge test campaign has been carried out for more than 5 years in order to build up a database composed of 19,000 penetration tests including endoscopic video record on the French railway network. The main objective of this work is to give a first statistical analysis of cone resistance in the coarse granular layer which represents a major component of railway track: the ballast. The results show that the cone resistance (qd increases with depth and presents strong variations corresponding to layers of different natures identified using the endoscopic records. In the first zone corresponding to the top 30cm, (qd increases linearly with a slope of around 1MPa/cm for fresh ballast and fouled ballast. In the second zone below 30cm deep, (qd increases more slowly with a slope of around 0,3MPa/cm and decreases below 50cm. These results show that there is no clear difference between fresh and fouled ballast. Hence, the (qd sensitivity is important and increases with depth. The (qd distribution for a set of tests does not follow a normal distribution. In the upper 30cm layer of ballast of track, data statistical treatment shows that train load and speed do not have any significant impact on the (qd distribution for clean ballast; they increase by 50% the average value of (qd for fouled ballast and increase the thickness as well. Below the 30cm upper layer, train load and speed have a clear impact on the (qd distribution.
Vector field statistical analysis of kinematic and force trajectories.
Pataky, Todd C; Robinson, Mark A; Vanrenterghem, Jos
2013-09-27
When investigating the dynamics of three-dimensional multi-body biomechanical systems it is often difficult to derive spatiotemporally directed predictions regarding experimentally induced effects. A paradigm of 'non-directed' hypothesis testing has emerged in the literature as a result. Non-directed analyses typically consist of ad hoc scalar extraction, an approach which substantially simplifies the original, highly multivariate datasets (many time points, many vector components). This paper describes a commensurately multivariate method as an alternative to scalar extraction. The method, called 'statistical parametric mapping' (SPM), uses random field theory to objectively identify field regions which co-vary significantly with the experimental design. We compared SPM to scalar extraction by re-analyzing three publicly available datasets: 3D knee kinematics, a ten-muscle force system, and 3D ground reaction forces. Scalar extraction was found to bias the analyses of all three datasets by failing to consider sufficient portions of the dataset, and/or by failing to consider covariance amongst vector components. SPM overcame both problems by conducting hypothesis testing at the (massively multivariate) vector trajectory level, with random field corrections simultaneously accounting for temporal correlation and vector covariance. While SPM has been widely demonstrated to be effective for analyzing 3D scalar fields, the current results are the first to demonstrate its effectiveness for 1D vector field analysis. It was concluded that SPM offers a generalized, statistically comprehensive solution to scalar extraction's over-simplification of vector trajectories, thereby making it useful for objectively guiding analyses of complex biomechanical systems. © 2013 Published by Elsevier Ltd. All rights reserved.
RNA STRAND: The RNA Secondary Structure and Statistical Analysis Database
Directory of Open Access Journals (Sweden)
Andronescu Mirela
2008-08-01
Full Text Available Abstract Background The ability to access, search and analyse secondary structures of a large set of known RNA molecules is very important for deriving improved RNA energy models, for evaluating computational predictions of RNA secondary structures and for a better understanding of RNA folding. Currently there is no database that can easily provide these capabilities for almost all RNA molecules with known secondary structures. Results In this paper we describe RNA STRAND – the RNA secondary STRucture and statistical ANalysis Database, a curated database containing known secondary structures of any type and organism. Our new database provides a wide collection of known RNA secondary structures drawn from public databases, searchable and downloadable in a common format. Comprehensive statistical information on the secondary structures in our database is provided using the RNA Secondary Structure Analyser, a new tool we have developed to analyse RNA secondary structures. The information thus obtained is valuable for understanding to which extent and with which probability certain structural motifs can appear. We outline several ways in which the data provided in RNA STRAND can facilitate research on RNA structure, including the improvement of RNA energy models and evaluation of secondary structure prediction programs. In order to keep up-to-date with new RNA secondary structure experiments, we offer the necessary tools to add solved RNA secondary structures to our database and invite researchers to contribute to RNA STRAND. Conclusion RNA STRAND is a carefully assembled database of trusted RNA secondary structures, with easy on-line tools for searching, analyzing and downloading user selected entries, and is publicly available at http://www.rnasoft.ca/strand.
Multivariate meta-analysis: a robust approach based on the theory of U-statistic.
Ma, Yan; Mazumdar, Madhu
2011-10-30
Meta-analysis is the methodology for combining findings from similar research studies asking the same question. When the question of interest involves multiple outcomes, multivariate meta-analysis is used to synthesize the outcomes simultaneously taking into account the correlation between the outcomes. Likelihood-based approaches, in particular restricted maximum likelihood (REML) method, are commonly utilized in this context. REML assumes a multivariate normal distribution for the random-effects model. This assumption is difficult to verify, especially for meta-analysis with small number of component studies. The use of REML also requires iterative estimation between parameters, needing moderately high computation time, especially when the dimension of outcomes is large. A multivariate method of moments (MMM) is available and is shown to perform equally well to REML. However, there is a lack of information on the performance of these two methods when the true data distribution is far from normality. In this paper, we propose a new nonparametric and non-iterative method for multivariate meta-analysis on the basis of the theory of U-statistic and compare the properties of these three procedures under both normal and skewed data through simulation studies. It is shown that the effect on estimates from REML because of non-normal data distribution is marginal and that the estimates from MMM and U-statistic-based approaches are very similar. Therefore, we conclude that for performing multivariate meta-analysis, the U-statistic estimation procedure is a viable alternative to REML and MMM. Easy implementation of all three methods are illustrated by their application to data from two published meta-analysis from the fields of hip fracture and periodontal disease. We discuss ideas for future research based on U-statistic for testing significance of between-study heterogeneity and for extending the work to meta-regression setting. Copyright © 2011 John Wiley & Sons, Ltd.
Jeffrey J. Green; Courtenay C. Stone; Abera Zegeye; Thomas A. Charles
2008-01-01
Because statistical analysis requires both familiarity with and the ability to use mathematics, students typically are required to take one or more prerequisite math courses prior to enrolling in the business statistics course. Despite these math prerequisites, however, students find it extremely difficult to learn business statistics. In this study, we use an ordered probit model to examine the effect of alternative prerequisite math course sequences on the grade performance of 1,684 busines...
MacIsaac, Rachael L.; Khatri, Pooja; Bendszus, Martin; Bracard, Serge; Broderick, Joseph; Campbell, Bruce; Ciccone, Alfonso; Dávalos, Antoni; Davis, Stephen M.; Demchuk, Andrew; Diener, Hans-Christoph; Dippel, Diederik; Donnan, Geoffrey A.; Fiehler, Jens; Fiorella, David; Goyal, Mayank; Hacke, Werner; Hill, Michael D.; Jahan, Reza; Jauch, Edward; Jovin, Tudor; Kidwell, Chelsea S.; Liebeskind, David; Majoie, Charles B.; Martins, Sheila Cristina Ouriques; Mitchell, Peter; Mocco, J.; Muir, Keith W.; Nogueira, Raul; Saver, Jeffrey L.; Schonewille, Wouter J.; Siddiqui, Adnan H.; Thomalla, Götz; Tomsick, Thomas A.; Turk, Aquilla S.; White, Philip; Zaidat, Osama; Lees, Kennedy R.
2015-01-01
Endovascular treatment has been shown to restore blood flow effectively. Second-generation medical devices such as stent retrievers are now showing overwhelming efficacy in clinical trials, particularly in conjunction with intravenous recombinant tissue plasminogen activator. This statistical
The Inappropriate Symmetries of Multivariate Statistical Analysis in Geometric Morphometrics.
Bookstein, Fred L
In today's geometric morphometrics the commonest multivariate statistical procedures, such as principal component analysis or regressions of Procrustes shape coordinates on Centroid Size, embody a tacit roster of symmetries -axioms concerning the homogeneity of the multiple spatial domains or descriptor vectors involved-that do not correspond to actual biological fact. These techniques are hence inappropriate for any application regarding which we have a-priori biological knowledge to the contrary (e.g., genetic/morphogenetic processes common to multiple landmarks, the range of normal in anatomy atlases, the consequences of growth or function for form). But nearly every morphometric investigation is motivated by prior insights of this sort. We therefore need new tools that explicitly incorporate these elements of knowledge, should they be quantitative, to break the symmetries of the classic morphometric approaches. Some of these are already available in our literature but deserve to be known more widely: deflated (spatially adaptive) reference distributions of Procrustes coordinates, Sewall Wright's century-old variant of factor analysis, the geometric algebra of importing explicit biomechanical formulas into Procrustes space. Other methods, not yet fully formulated, might involve parameterized models for strain in idealized forms under load, principled approaches to the separation of functional from Brownian aspects of shape variation over time, and, in general, a better understanding of how the formalism of landmarks interacts with the many other approaches to quantification of anatomy. To more powerfully organize inferences from the high-dimensional measurements that characterize so much of today's organismal biology, tomorrow's toolkit must rely neither on principal component analysis nor on the Procrustes distance formula, but instead on sound prior biological knowledge as expressed in formulas whose coefficients are not all the same. I describe the problems
ROOT - A C++ Framework for Petabyte Data Storage, Statistical Analysis and Visualization
Naumann, Axel; Ballintijn, Maarten; Bellenot, Bertrand; Biskup, Marek; Brun, Rene; Buncic, Nenad; Canal, Philippe; Casadei, Diego; Couet, Olivier; Fine, Valery; Franco, Leandro; Ganis, Gerardo; Gheata, Andrei; Gonzalez~Maline, David; Goto, Masaharu; Iwaszkiewicz, Jan; Kreshuk, Anna; Marcos Segura, Diego; Maunder, Richard; Moneta, Lorenzo; Offermann, Eddy; Onuchin, Valeriy; Panacek, Suzanne; Rademakers, Fons; Russo, Paul; Tadel, Matevz
2009-01-01
ROOT is an object-oriented C++ framework conceived in the high-energy physics (HEP) community, designed for storing and analyzing petabytes of data in an efficient way. Any instance of a C++ class can be stored into a ROOT file in a machine-independent compressed binary format. In ROOT the TTree object container is optimized for statistical data analysis over very large data sets by using vertical data storage techniques. These containers can span a large number of files on local disks, the web, or a number of different shared file systems. In order to analyze this data, the user can chose out of a wide set of mathematical and statistical functions, including linear algebra classes, numerical algorithms such as integration and minimization, and various methods for performing regression analysis (fitting). In particular, the RooFit package allows the user to perform complex data modeling and fitting while the RooStats library provides abstractions and implementations for advance...
Fuel performance analysis code 'FAIR'
International Nuclear Information System (INIS)
Swami Prasad, P.; Dutta, B.K.; Kushwaha, H.S.; Mahajan, S.C.; Kakodkar, A.
1994-01-01
For modelling nuclear reactor fuel rod behaviour of water cooled reactors under severe power maneuvering and high burnups, a mechanistic fuel performance analysis code FAIR has been developed. The code incorporates finite element based thermomechanical module, physically based fission gas release module and relevant models for modelling fuel related phenomena, such as, pellet cracking, densification and swelling, radial flux redistribution across the pellet due to the build up of plutonium near the pellet surface, pellet clad mechanical interaction/stress corrosion cracking (PCMI/SSC) failure of sheath etc. The code follows the established principles of fuel rod analysis programmes, such as coupling of thermal and mechanical solutions along with the fission gas release calculations, analysing different axial segments of fuel rod simultaneously, providing means for performing local analysis such as clad ridging analysis etc. The modular nature of the code offers flexibility in affecting modifications easily to the code for modelling MOX fuels and thorium based fuels. For performing analysis of fuel rods subjected to very long power histories within a reasonable amount of time, the code has been parallelised and is commissioned on the ANUPAM parallel processing system developed at Bhabha Atomic Research Centre (BARC). (author). 37 refs
Statistical Analysis of Data with Non-Detectable Values
Energy Technology Data Exchange (ETDEWEB)
Frome, E.L.
2004-08-26
Environmental exposure measurements are, in general, positive and may be subject to left censoring, i.e. the measured value is less than a ''limit of detection''. In occupational monitoring, strategies for assessing workplace exposures typically focus on the mean exposure level or the probability that any measurement exceeds a limit. A basic problem of interest in environmental risk assessment is to determine if the mean concentration of an analyte is less than a prescribed action level. Parametric methods, used to determine acceptable levels of exposure, are often based on a two parameter lognormal distribution. The mean exposure level and/or an upper percentile (e.g. the 95th percentile) are used to characterize exposure levels, and upper confidence limits are needed to describe the uncertainty in these estimates. In certain situations it is of interest to estimate the probability of observing a future (or ''missed'') value of a lognormal variable. Statistical methods for random samples (without non-detects) from the lognormal distribution are well known for each of these situations. In this report, methods for estimating these quantities based on the maximum likelihood method for randomly left censored lognormal data are described and graphical methods are used to evaluate the lognormal assumption. If the lognormal model is in doubt and an alternative distribution for the exposure profile of a similar exposure group is not available, then nonparametric methods for left censored data are used. The mean exposure level, along with the upper confidence limit, is obtained using the product limit estimate, and the upper confidence limit on the 95th percentile (i.e. the upper tolerance limit) is obtained using a nonparametric approach. All of these methods are well known but computational complexity has limited their use in routine data analysis with left censored data. The recent development of the R environment for statistical
THE ANALYSIS OF STATISTICAL DATA ON MALIGNANT NEOPLASMS ASSOCIATED WITH HUMAN P APILLOMAVIRUS
Directory of Open Access Journals (Sweden)
A. A. Kostin
2016-01-01
Full Text Available In this study of statistical data for the first time in Russia the analysis of the morbidity and mortality of patients with malignant neoplasms that may be associated with human papilloma virus (HPV is performed: cervical cancer (cervical cancer, cancer of the vulva and vagina, cancer of penis, cancer of the rectum, anal canal and rectosigmoid junction cancer, cancer of the pharynx and larynx.
Black, Joshua A.; Knowles, Peter J.
2018-06-01
The performance of quasi-variational coupled-cluster (QV) theory applied to the calculation of activation and reaction energies has been investigated. A statistical analysis of results obtained for six different sets of reactions has been carried out, and the results have been compared to those from standard single-reference methods. In general, the QV methods lead to increased activation energies and larger absolute reaction energies compared to those obtained with traditional coupled-cluster theory.
Kiekkas, Panagiotis; Panagiotarou, Aliki; Malja, Alvaro; Tahirai, Daniela; Zykai, Rountina; Bakalis, Nick; Stefanopoulos, Nikolaos
2015-12-01
Although statistical knowledge and skills are necessary for promoting evidence-based practice, health sciences students have expressed anxiety about statistics courses, which may hinder their learning of statistical concepts. To evaluate the effects of a biostatistics course on nursing students' attitudes toward statistics and to explore the association between these attitudes and their performance in the course examination. One-group quasi-experimental pre-test/post-test design. Undergraduate nursing students of the fifth or higher semester of studies, who attended a biostatistics course. Participants were asked to complete the pre-test and post-test forms of The Survey of Attitudes Toward Statistics (SATS)-36 scale at the beginning and end of the course respectively. Pre-test and post-test scale scores were compared, while correlations between post-test scores and participants' examination performance were estimated. Among 156 participants, post-test scores of the overall SATS-36 scale and of the Affect, Cognitive Competence, Interest and Effort components were significantly higher than pre-test ones, indicating that the course was followed by more positive attitudes toward statistics. Among 104 students who participated in the examination, higher post-test scores of the overall SATS-36 scale and of the Affect, Difficulty, Interest and Effort components were significantly but weakly correlated with higher examination performance. Students' attitudes toward statistics can be improved through appropriate biostatistics courses, while positive attitudes contribute to higher course achievements and possibly to improved statistical skills in later professional life. Copyright © 2015 Elsevier Ltd. All rights reserved.
Analysis and Evaluation of Statistical Models for Integrated Circuits Design
Directory of Open Access Journals (Sweden)
Sáenz-Noval J.J.
2011-10-01
Full Text Available Statistical models for integrated circuits (IC allow us to estimate the percentage of acceptable devices in the batch before fabrication. Actually, Pelgrom is the statistical model most accepted in the industry; however it was derived from a micrometer technology, which does not guarantee reliability in nanometric manufacturing processes. This work considers three of the most relevant statistical models in the industry and evaluates their limitations and advantages in analog design, so that the designer has a better criterion to make a choice. Moreover, it shows how several statistical models can be used for each one of the stages and design purposes.
Plutonium metal exchange program : current status and statistical analysis
Energy Technology Data Exchange (ETDEWEB)
Tandon, L. (Lav); Eglin, J. L. (Judith Lynn); Michalak, S. E. (Sarah E.); Picard, R. R.; Temer, D. J. (Donald J.)
2004-01-01
The Rocky Flats Plutonium (Pu) Metal Sample Exchange program was conducted to insure the quality and intercomparability of measurements such as Pu assay, Pu isotopics, and impurity analyses. The Rocky Flats program was discontinued in 1989 after more than 30 years. In 2001, Los Alamos National Laboratory (LANL) reestablished the Pu Metal Exchange program. In addition to the Atomic Weapons Establishment (AWE) at Aldermaston, six Department of Energy (DOE) facilities Argonne East, Argonne West, Livermore, Los Alamos, New Brunswick Laboratory, and Savannah River are currently participating in the program. Plutonium metal samples are prepared and distributed to the sites for destructive measurements to determine elemental concentration, isotopic abundance, and both metallic and nonmetallic impurity levels. The program provides independent verification of analytical measurement capabilies for each participating facility and allows problems in analytical methods to be identified. The current status of the program will be discussed with emphasis on the unique statistical analysis and modeling of the data developed for the program. The discussion includes the definition of the consensus values for each analyte (in the presence and absence of anomalous values and/or censored values), and interesting features of the data and the results.
Corrected Statistical Energy Analysis Model for Car Interior Noise
Directory of Open Access Journals (Sweden)
A. Putra
2015-01-01
Full Text Available Statistical energy analysis (SEA is a well-known method to analyze the flow of acoustic and vibration energy in a complex structure. For an acoustic space where significant absorptive materials are present, direct field component from the sound source dominates the total sound field rather than a reverberant field, where the latter becomes the basis in constructing the conventional SEA model. Such environment can be found in a car interior and thus a corrected SEA model is proposed here to counter this situation. The model is developed by eliminating the direct field component from the total sound field and only the power after the first reflection is considered. A test car cabin was divided into two subsystems and by using a loudspeaker as a sound source, the power injection method in SEA was employed to obtain the corrected coupling loss factor and the damping loss factor from the corrected SEA model. These parameters were then used to predict the sound pressure level in the interior cabin using the injected input power from the engine. The results show satisfactory agreement with the directly measured SPL.
Multivariate statistical analysis - an application to lunar materials
International Nuclear Information System (INIS)
Deb, M.
1978-01-01
The compositional characteristics of clinopyroxenes and spinels - two minerals considered to be very useful in deciphering lunar history, have been studied using the multivariate statistical method of principal component analysis. The mineral-chemical data used are from certain lunar rocks and fines collected by Apollo 11, 12, 14 and 15 and Luna 16 and 20 missions, representing mainly the mare basalts and also non-mare basalts, breccia and rock fragments from the highland regions, in which a large number of these minerals have been analyzed. The correlations noted in the mineral compositions, indicating substitutional relationships, have been interpreted on the basis of available crystal-chemical and petrological informations. Compositional trends for individual specimens have been delineated and compared by producing ''principal latent vector diagrams''. The percent variance of the principal components denoted by the eigenvalues, have been evaluated in terms of the crystallization history of the samples. Some of the major petrogenetic implications of this study concern the role of early formed cumulate phases in the near-surface fractionation of mare basalts, mixing of mineral compositions in the highland regolith and the subsolidus reduction trends in lunar spinels. (auth.)
International Nuclear Information System (INIS)
Lommers, L.J.; Parme, L.L.; Shenoy, A.S.
1995-07-01
This paper describes a statistical approach for determining the impact of system performance and design uncertainties on power plant performance. The objectives of this design approach are to ensure that adequate margin is provided, that excess margin is minimized, and that full advantage can be taken of unconsumed margin. It is applicable to any thermal system in which these factors are important. The method is demonstrated using the Gas Turbine Modular Helium Reactor as an example. The quantitative approach described allows the characterization of plant performance and the specification of the system design requirements necessary to achieve the desired performance with high confidence. Performance variations due to design evolution, inservice degradation, and basic performance uncertainties are considered. The impact of all performance variabilities is combined using Monte Carlo analysis to predict the range of expected operation
STATISTICAL ANALYSIS OF DAMAGEABILITY OF THE BYPASS ENGINES COMPRESSOR BLADES
Directory of Open Access Journals (Sweden)
Boris A. Chichkov
2018-01-01
Full Text Available Aircraft gas turbine engines during the operation are exposed to damage of flowing parts. The elements of the engine design, appreciably determining operational characteristics are rotor blades. Character of typical damages for various types of engines depends on appointment and a geographical place of the aircraft operation on which one or another engine is installed. For example, the greatest problem for turboshaft engines operated in the dusty air conditions is erosive wear of a rotor blade airfoil. Among principal causes of flowing parts damages of bypass engine compressors are foreign object damages. Independently there are the damages caused by fatigue of a rotor blade material at dangerous blade mode. Pieces of the ice formed in the input unit, birds and the like can also be a source of danger. The foreign objects getting into the engine from runway are nuts, bolts, pieces of tire protectors, lock-wire, elements from earlier flying off aircraft, etc. The entry of foreign objects into the engine depends on both an operation mode (during the operation on the ground, on takeoff, on landing roll using the reverse and so on, and the aircraft engine position.Thus the foreign objects entered into the flowing path of bypass engine damage blade cascade of low and high pressure. Foreign objects entered into the flowing part of the engine with rotor blades result in dents on edges and blade shroud, deformations of edges, breakage, camber of peripheral parts and are distributed "nonlinear" on path length (steps. The article presents the results of the statistical analysis of three types engine compressors damageability over the period of more than three years. Damages are divided according to types of engines in whole and to their separate steps, depths and lengths, blades damage location. The results of the analysis make it possible to develop recommendations to carry out the optical-visual control procedures.
Statistical Analysis of Development Trends in Global Renewable Energy
Directory of Open Access Journals (Sweden)
Marina D. Simonova
2016-01-01
Full Text Available The article focuses on the economic and statistical analysis of industries associated with the use of renewable energy sources in several countries. The dynamic development and implementation of technologies based on renewable energy sources (hereinafter RES is the defining trend of world energy development. The uneven distribution of hydrocarbon reserves, increasing demand of developing countries and environmental risks associated with the production and consumption of fossil resources has led to an increasing interest of many states to this field. Creating low-carbon economies involves the implementation of plans to increase the proportion of clean energy through renewable energy sources, energy efficiency, reduce greenhouse gas emissions. The priority of this sector is a characteristic feature of modern development of developed (USA, EU, Japan and emerging economies (China, India, Brazil, etc., as evidenced by the inclusion of the development of this segment in the state energy strategies and the revision of existing approaches to energy security. The analysis of the use of renewable energy, its contribution to value added of countries-producers is of a particular interest. Over the last decade, the share of energy produced from renewable sources in the energy balances of the world's largest economies increased significantly. Every year the number of power generating capacity based on renewable energy is growing, especially, this trend is apparent in China, USA and European Union countries. There is a significant increase in direct investment in renewable energy. The total investment over the past ten years increased by 5.6 times. The most rapidly developing kinds are solar energy and wind power.
TECHNIQUE OF THE STATISTICAL ANALYSIS OF INVESTMENT APPEAL OF THE REGION
Directory of Open Access Journals (Sweden)
А. А. Vershinina
2014-01-01
Full Text Available The technique of the statistical analysis of investment appeal of the region is given in scientific article for direct foreign investments. Definition of a technique of the statistical analysis is given, analysis stages reveal, the mathematico-statistical tools are considered.
SeDA: A software package for the statistical analysis of the instrument drift
International Nuclear Information System (INIS)
Lee, H. J.; Jang, S. C.; Lim, T. J.
2006-01-01
The setpoints for safety-related equipment are affected by many sources of an uncertainty. ANSI/ISA-S67.04.01-2000 [1] and ISA-RP6 7.04.02-2000 [2] suggested the statistical approaches for ensuring that the safety-related instrument setpoints were established and maintained within the technical specification limits [3]. However, Jang et al. [4] indicated that the preceding methodologies for a setpoint drift analysis might be insufficient to manage a setpoint drift on an instrumentation device and proposed new statistical analysis procedures for the management of a setpoint drift, based on the plant specific as-found/as-left data. Although IHPA (Instrument History Performance Analysis) is a widely known commercial software package to analyze an instrument setpoint drift, several steps in the new procedure cannot be performed by using it because it is based on the statistical approaches suggested in the ANSI/ISA-S67.04.01 -2000 [1] and ISA-RP67.04.02-2000 [2], In this paper we present a software package (SeDA: Setpoint Drift Analysis) that implements new methodologies, and which is easy to use, as it is accompanied by powerful graphical tools. (authors)
GIS and statistical analysis for landslide susceptibility mapping in the Daunia area, Italy
Mancini, F.; Ceppi, C.; Ritrovato, G.
2010-09-01
This study focuses on landslide susceptibility mapping in the Daunia area (Apulian Apennines, Italy) and achieves this by using a multivariate statistical method and data processing in a Geographical Information System (GIS). The Logistic Regression (hereafter LR) method was chosen to produce a susceptibility map over an area of 130 000 ha where small settlements are historically threatened by landslide phenomena. By means of LR analysis, the tendency to landslide occurrences was, therefore, assessed by relating a landslide inventory (dependent variable) to a series of causal factors (independent variables) which were managed in the GIS, while the statistical analyses were performed by means of the SPSS (Statistical Package for the Social Sciences) software. The LR analysis produced a reliable susceptibility map of the investigated area and the probability level of landslide occurrence was ranked in four classes. The overall performance achieved by the LR analysis was assessed by local comparison between the expected susceptibility and an independent dataset extrapolated from the landslide inventory. Of the samples classified as susceptible to landslide occurrences, 85% correspond to areas where landslide phenomena have actually occurred. In addition, the consideration of the regression coefficients provided by the analysis demonstrated that a major role is played by the "land cover" and "lithology" causal factors in determining the occurrence and distribution of landslide phenomena in the Apulian Apennines.
Techniques for Automated Performance Analysis
Energy Technology Data Exchange (ETDEWEB)
Marcus, Ryan C. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
2014-09-02
The performance of a particular HPC code depends on a multitude of variables, including compiler selection, optimization flags, OpenMP pool size, file system load, memory usage, MPI configuration, etc. As a result of this complexity, current predictive models have limited applicability, especially at scale. We present a formulation of scientific codes, nodes, and clusters that reduces complex performance analysis to well-known mathematical techniques. Building accurate predictive models and enhancing our understanding of scientific codes at scale is an important step towards exascale computing.
Directory of Open Access Journals (Sweden)
Shirin Iranfar
2013-12-01
Full Text Available Introduction: Test anxiety is a common phenomenon among students and is one of the problems of educational system. The present study was conducted to investigate the test anxiety in vital statistics course and its association with academic performance of students at Kermanshah University of Medical Sciences. This study was descriptive-analytical and the study sample included the students studying in nursing and midwifery, paramedicine and health faculties that had taken vital statistics course and were selected through census method. Sarason questionnaire was used to analyze the test anxiety. Data were analyzed by descriptive and inferential statistics. The findings indicated no significant correlation between test anxiety and score of vital statistics course.
Development of a statistical shape model of multi-organ and its performance evaluation
International Nuclear Information System (INIS)
Nakada, Misaki; Shimizu, Akinobu; Kobatake, Hidefumi; Nawano, Shigeru
2010-01-01
Existing statistical shape modeling methods for an organ can not take into account the correlation between neighboring organs. This study focuses on a level set distribution model and proposes two modeling methods for multiple organs that can take into account the correlation between neighboring organs. The first method combines level set functions of multiple organs into a vector. Subsequently it analyses the distribution of the vectors of a training dataset by a principal component analysis and builds a multiple statistical shape model. Second method constructs a statistical shape model for each organ independently and assembles component scores of different organs in a training dataset so as to generate a vector. It analyses the distribution of the vectors of to build a statistical shape model of multiple organs. This paper shows results of applying the proposed methods trained by 15 abdominal CT volumes to unknown 8 CT volumes. (author)
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
HORIZONTAL BRANCH MORPHOLOGY OF GLOBULAR CLUSTERS: A MULTIVARIATE STATISTICAL ANALYSIS
International Nuclear Information System (INIS)
Jogesh Babu, G.; Chattopadhyay, Tanuka; Chattopadhyay, Asis Kumar; Mondal, Saptarshi
2009-01-01
The proper interpretation of horizontal branch (HB) morphology is crucial to the understanding of the formation history of stellar populations. In the present study a multivariate analysis is used (principal component analysis) for the selection of appropriate HB morphology parameter, which, in our case, is the logarithm of effective temperature extent of the HB (log T effHB ). Then this parameter is expressed in terms of the most significant observed independent parameters of Galactic globular clusters (GGCs) separately for coherent groups, obtained in a previous work, through a stepwise multiple regression technique. It is found that, metallicity ([Fe/H]), central surface brightness (μ v ), and core radius (r c ) are the significant parameters to explain most of the variations in HB morphology (multiple R 2 ∼ 0.86) for GGC elonging to the bulge/disk while metallicity ([Fe/H]) and absolute magnitude (M v ) are responsible for GGC belonging to the inner halo (multiple R 2 ∼ 0.52). The robustness is tested by taking 1000 bootstrap samples. A cluster analysis is performed for the red giant branch (RGB) stars of the GGC belonging to Galactic inner halo (Cluster 2). A multi-episodic star formation is preferred for RGB stars of GGC belonging to this group. It supports the asymptotic giant branch (AGB) model in three episodes instead of two as suggested by Carretta et al. for halo GGC while AGB model is suggested to be revisited for bulge/disk GGC.
Ceppi, Marcello; Gallo, Fabio; Bonassi, Stefano
2011-01-01
The most common study design performed in population studies based on the micronucleus (MN) assay, is the cross-sectional study, which is largely performed to evaluate the DNA damaging effects of exposure to genotoxic agents in the workplace, in the environment, as well as from diet or lifestyle factors. Sample size is still a critical issue in the design of MN studies since most recent studies considering gene-environment interaction, often require a sample size of several hundred subjects, which is in many cases difficult to achieve. The control of confounding is another major threat to the validity of causal inference. The most popular confounders considered in population studies using MN are age, gender and smoking habit. Extensive attention is given to the assessment of effect modification, given the increasing inclusion of biomarkers of genetic susceptibility in the study design. Selected issues concerning the statistical treatment of data have been addressed in this mini-review, starting from data description, which is a critical step of statistical analysis, since it allows to detect possible errors in the dataset to be analysed and to check the validity of assumptions required for more complex analyses. Basic issues dealing with statistical analysis of biomarkers are extensively evaluated, including methods to explore the dose-response relationship among two continuous variables and inferential analysis. A critical approach to the use of parametric and non-parametric methods is presented, before addressing the issue of most suitable multivariate models to fit MN data. In the last decade, the quality of statistical analysis of MN data has certainly evolved, although even nowadays only a small number of studies apply the Poisson model, which is the most suitable method for the analysis of MN data.
Cellular Analysis of Boltzmann Most Probable Ideal Gas Statistics
Cahill, Michael E.
2018-04-01
Exact treatment of Boltzmann's Most Probable Statistics for an Ideal Gas of Identical Mass Particles having Translational Kinetic Energy gives a Distribution Law for Velocity Phase Space Cell j which relates the Particle Energy and the Particle Population according toB e(j) = A - Ψ(n(j) + 1)where A & B are the Lagrange Multipliers and Ψ is the Digamma Function defined byΨ(x + 1) = d/dx ln(x!)A useful sufficiently accurate approximation for Ψ is given byΨ(x +1) ≈ ln(e-γ + x)where γ is the Euler constant (≈.5772156649) & so the above distribution equation is approximatelyB e(j) = A - ln(e-γ + n(j))which can be inverted to solve for n(j) givingn(j) = (eB (eH - e(j)) - 1) e-γwhere B eH = A + γ& where B eH is a unitless particle energy which replaces the parameter A. The 2 approximate distribution equations imply that eH is the highest particle energy and the highest particle population isnH = (eB eH - 1) e-γwhich is due to the facts that population becomes negative if e(j) > eH and kinetic energy becomes negative if n(j) > nH.An explicit construction of Cells in Velocity Space which are equal in volume and homogeneous for almost all cells is shown to be useful in the analysis.Plots for sample distribution properties using e(j) as the independent variable are presented.
Directory of Open Access Journals (Sweden)
Rawid Banchuin
2014-01-01
Full Text Available In this research, the analysis of statistical variations in subthreshold MOSFET's high frequency characteristics defined in terms of gate capacitance and transition frequency, have been shown and the resulting comprehensive analytical models of such variations in terms of their variances have been proposed. Major imperfection in the physical level properties including random dopant fluctuation and effects of variations in MOSFET's manufacturing process, have been taken into account in the proposed analysis and modeling. The up to dated comprehensive analytical model of statistical variation in MOSFET's parameter has been used as the basis of analysis and modeling. The resulting models have been found to be both analytic and comprehensive as they are the precise mathematical expressions in terms of physical level variables of MOSFET. Furthermore, they have been verified at the nanometer level by using 65~nm level BSIM4 based benchmarks and have been found to be very accurate with smaller than 5 % average percentages of errors. Hence, the performed analysis gives the resulting models which have been found to be the potential mathematical tool for the statistical and variability aware analysis and design of subthreshold MOSFET based VHF circuits, systems and applications.
Effect of the absolute statistic on gene-sampling gene-set analysis methods.
Nam, Dougu
2017-06-01
Gene-set enrichment analysis and its modified versions have commonly been used for identifying altered functions or pathways in disease from microarray data. In particular, the simple gene-sampling gene-set analysis methods have been heavily used for datasets with only a few sample replicates. The biggest problem with this approach is the highly inflated false-positive rate. In this paper, the effect of absolute gene statistic on gene-sampling gene-set analysis methods is systematically investigated. Thus far, the absolute gene statistic has merely been regarded as a supplementary method for capturing the bidirectional changes in each gene set. Here, it is shown that incorporating the absolute gene statistic in gene-sampling gene-set analysis substantially reduces the false-positive rate and improves the overall discriminatory ability. Its effect was investigated by power, false-positive rate, and receiver operating curve for a number of simulated and real datasets. The performances of gene-set analysis methods in one-tailed (genome-wide association study) and two-tailed (gene expression data) tests were also compared and discussed.
Energy Technology Data Exchange (ETDEWEB)
Kančev, Duško, E-mail: dusko.kancev@ec.europa.eu [European Commission, DG-JRC, Institute for Energy and Transport, P.O. Box 2, NL-1755 ZG Petten (Netherlands); Duchac, Alexander; Zerger, Benoit [European Commission, DG-JRC, Institute for Energy and Transport, P.O. Box 2, NL-1755 ZG Petten (Netherlands); Maqua, Michael [Gesellschaft für Anlagen-und-Reaktorsicherheit (GRS) mbH, Schwetnergasse 1, 50667 Köln (Germany); Wattrelos, Didier [Institut de Radioprotection et de Sûreté Nucléaire (IRSN), BP 17 - 92262 Fontenay-aux-Roses Cedex (France)
2014-07-01
Highlights: • Analysis of operating experience related to emergency diesel generators events at NPPs. • Four abundant operating experience databases screened. • Delineating important insights and conclusions based on the operating experience. - Abstract: This paper is aimed at studying the operating experience related to emergency diesel generators (EDGs) events at nuclear power plants collected from the past 20 years. Events related to EDGs failures and/or unavailability as well as all the supporting equipment are in the focus of the analysis. The selected operating experience was analyzed in detail in order to identify the type of failures, attributes that contributed to the failure, failure modes potential or real, discuss risk relevance, summarize important lessons learned, and provide recommendations. The study in this particular paper is tightly related to the performing of statistical analysis of the operating experience. For the purpose of this study EDG failure is defined as EDG failure to function on demand (i.e. fail to start, fail to run) or during testing, or an unavailability of an EDG, except of unavailability due to regular maintenance. The Gesellschaft für Anlagen und Reaktorsicherheit mbH (GRS) and Institut de Radioprotection et de Sûreté Nucléaire (IRSN) databases as well as the operating experience contained in the IAEA/NEA International Reporting System for Operating Experience and the U.S. Licensee Event Reports were screened. The screening methodology applied for each of the four different databases is presented. Further on, analysis aimed at delineating the causes, root causes, contributing factors and consequences are performed. A statistical analysis was performed related to the chronology of events, types of failures, the operational circumstances of detection of the failure and the affected components/subsystems. The conclusions and results of the statistical analysis are discussed. The main findings concerning the testing
International Nuclear Information System (INIS)
Kančev, Duško; Duchac, Alexander; Zerger, Benoit; Maqua, Michael; Wattrelos, Didier
2014-01-01
Highlights: • Analysis of operating experience related to emergency diesel generators events at NPPs. • Four abundant operating experience databases screened. • Delineating important insights and conclusions based on the operating experience. - Abstract: This paper is aimed at studying the operating experience related to emergency diesel generators (EDGs) events at nuclear power plants collected from the past 20 years. Events related to EDGs failures and/or unavailability as well as all the supporting equipment are in the focus of the analysis. The selected operating experience was analyzed in detail in order to identify the type of failures, attributes that contributed to the failure, failure modes potential or real, discuss risk relevance, summarize important lessons learned, and provide recommendations. The study in this particular paper is tightly related to the performing of statistical analysis of the operating experience. For the purpose of this study EDG failure is defined as EDG failure to function on demand (i.e. fail to start, fail to run) or during testing, or an unavailability of an EDG, except of unavailability due to regular maintenance. The Gesellschaft für Anlagen und Reaktorsicherheit mbH (GRS) and Institut de Radioprotection et de Sûreté Nucléaire (IRSN) databases as well as the operating experience contained in the IAEA/NEA International Reporting System for Operating Experience and the U.S. Licensee Event Reports were screened. The screening methodology applied for each of the four different databases is presented. Further on, analysis aimed at delineating the causes, root causes, contributing factors and consequences are performed. A statistical analysis was performed related to the chronology of events, types of failures, the operational circumstances of detection of the failure and the affected components/subsystems. The conclusions and results of the statistical analysis are discussed. The main findings concerning the testing
Effects of Concept Mapping Strategy on Learning Performance in Business and Economics Statistics
Chiou, Chei-Chang
2009-01-01
A concept map (CM) is a hierarchically arranged, graphic representation of the relationships among concepts. Concept mapping (CMING) is the process of constructing a CM. This paper examines whether a CMING strategy can be useful in helping students to improve their learning performance in a business and economics statistics course. A single…
Bourne, Victoria J.
2018-01-01
Statistics anxiety is experienced by a large number of psychology students, and previous research has examined a range of potential correlates, including academic performance, mathematical ability and psychological predictors. These varying predictors are often considered separately, although there may be shared variance between them. In the…
Touchton, Michael
2015-01-01
I administer a quasi-experiment using undergraduate political science majors in statistics classes to evaluate whether "flipping the classroom" (the treatment) alters students' applied problem-solving performance and satisfaction relative to students in a traditional classroom environment (the control). I also assess whether general…
Jeffrey J. Green; Courtenay C. Stone; Abera Zegeye; Thomas A. Charles
2007-01-01
We use a binary probit model to assess the impact of several changes in math prerequisites on student performance in an undergraduate business statistics course. While the initial prerequisites did not necessarily provide students with the necessary math skills, our study, the first to examine the effect of math prerequisite changes, shows that these changes were deleterious to student performance. Our results helped convince the College of Business to change the math prerequisite again begin...
Mascaró, Maite; Sacristán, Ana Isabel; Rufino, Marta M.
2016-01-01
For the past 4 years, we have been involved in a project that aims to enhance the teaching and learning of experimental analysis and statistics, of environmental and biological sciences students, through computational programming activities (using R code). In this project, through an iterative design, we have developed sequences of R-code-based…
Ohyanagi, S.; Dileonardo, C.
2013-12-01
As a natural phenomenon earthquake occurrence is difficult to predict. Statistical analysis of earthquake data was performed using candlestick chart and Bollinger Band methods. These statistical methods, commonly used in the financial world to analyze market trends were tested against earthquake data. Earthquakes above Mw 4.0 located on shore of Sanriku (37.75°N ~ 41.00°N, 143.00°E ~ 144.50°E) from February 1973 to May 2013 were selected for analysis. Two specific patterns in earthquake occurrence were recognized through the analysis. One is a spread of candlestick prior to the occurrence of events greater than Mw 6.0. A second pattern shows convergence in the Bollinger Band, which implies a positive or negative change in the trend of earthquakes. Both patterns match general models for the buildup and release of strain through the earthquake cycle, and agree with both the characteristics of the candlestick chart and Bollinger Band analysis. These results show there is a high correlation between patterns in earthquake occurrence and trend analysis by these two statistical methods. The results of this study agree with the appropriateness of the application of these financial analysis methods to the analysis of earthquake occurrence.
Olive mill wastewater characteristics: modelling and statistical analysis
Directory of Open Access Journals (Sweden)
Martins-Dias, Susete
2004-09-01
Full Text Available A synthesis of the work carried out on Olive Mill Wastewater (OMW characterisation is given, covering articles published over the last 50 years. Data on OMW characterisation found in the literature are summarised and correlations between them and with phenolic compounds content are sought. This permits the characteristics of an OMW to be estimated from one simple measurement: the phenolic compounds concentration. A model based on OMW characterisations accounting 6 countries was developed along with a model for Portuguese OMW. The statistical analysis of the correlations obtained indicates that Chemical Oxygen Demand of a given OMW is a second-degree polynomial function of its phenolic compounds concentration. Tests to evaluate the regressions significance were carried out, based on multivariable ANOVA analysis, on visual standardised residuals distribution and their means for confidence levels of 95 and 99 %, validating clearly these models. This modelling work will help in the future planning, operation and monitoring of an OMW treatment plant.Presentamos una síntesis de los trabajos realizados en los últimos 50 años relacionados con la caracterización del alpechín. Realizamos una recopilación de los datos publicados, buscando correlaciones entre los datos relativos al alpechín y los compuestos fenólicos. Esto permite la determinación de las características del alpechín a partir de una sola medida: La concentración de compuestos fenólicos. Proponemos dos modelos, uno basado en datos relativos a seis países y un segundo aplicado únicamente a Portugal. El análisis estadístico de las correlaciones obtenidas indica que la demanda química de oxígeno de un determinado alpechín es una función polinómica de segundo grado de su concentración de compuestos fenólicos. Se comprobó la significancia de esta correlación mediante la aplicación del análisis multivariable ANOVA, y además se evaluó la distribución de residuos y sus
A statistical framework for differential network analysis from microarray data
Directory of Open Access Journals (Sweden)
Datta Somnath
2010-02-01
Full Text Available Abstract Background It has been long well known that genes do not act alone; rather groups of genes act in consort during a biological process. Consequently, the expression levels of genes are dependent on each other. Experimental techniques to detect such interacting pairs of genes have been in place for quite some time. With the advent of microarray technology, newer computational techniques to detect such interaction or association between gene expressions are being proposed which lead to an association network. While most microarray analyses look for genes that are differentially expressed, it is of potentially greater significance to identify how entire association network structures change between two or more biological settings, say normal versus diseased cell types. Results We provide a recipe for conducting a differential analysis of networks constructed from microarray data under two experimental settings. At the core of our approach lies a connectivity score that represents the strength of genetic association or interaction between two genes. We use this score to propose formal statistical tests for each of following queries: (i whether the overall modular structures of the two networks are different, (ii whether the connectivity of a particular set of "interesting genes" has changed between the two networks, and (iii whether the connectivity of a given single gene has changed between the two networks. A number of examples of this score is provided. We carried out our method on two types of simulated data: Gaussian networks and networks based on differential equations. We show that, for appropriate choices of the connectivity scores and tuning parameters, our method works well on simulated data. We also analyze a real data set involving normal versus heavy mice and identify an interesting set of genes that may play key roles in obesity. Conclusions Examining changes in network structure can provide valuable information about the
Statistical analysis of complex systems with nonclassical invariant measures
Fratalocchi, Andrea
2011-01-01
I investigate the problem of finding a statistical description of a complex many-body system whose invariant measure cannot be constructed stemming from classical thermodynamics ensembles. By taking solitons as a reference system and by employing a
Practical application and statistical analysis of titrimetric monitoring ...
African Journals Online (AJOL)
2008-09-18
Sep 18, 2008 ... The statistical tests showed that, depending on the titrant concentration ... The ASD process offers the possibility of transferring waste streams into ..... (1993) Weak acid/bases and pH control in anaerobic system – A review.
STATISTICAL ANALYSIS OF THE DEMOLITION OF THE HITCH DEVICES ELEMENTS
Directory of Open Access Journals (Sweden)
V. V. Artemchuk
2009-03-01
Full Text Available The results of statistical research of wear of automatic coupler body butts and thrust plates of electric locomotives are presented in the article. Due to the increased wear the mentioned elements require special attention.
Gregor Mendel's Genetic Experiments: A Statistical Analysis after 150 Years
Czech Academy of Sciences Publication Activity Database
Kalina, Jan
2016-01-01
Roč. 12, č. 2 (2016), s. 20-26 ISSN 1801-5603 Institutional support: RVO:67985807 Keywords : genetics * history of science * biostatistics * design of experiments Subject RIV: BB - Applied Statistics, Operational Research
International Nuclear Information System (INIS)
Vaganov, P.A.; Kol'tsov, A.A.; Kulikov, V.D.; Mejer, V.A.
1983-01-01
The multi-element instrumental neutron activation analysis of samples of mountain rocks (sandstones, aleurolites and shales of one of gold deposits) is performed. The spectra of irradiated samples are measured by Ge(Li) detector of the volume of 35 mm 3 . The content of 22 chemical elements is determined in each sample. The results of analysis serve as reliable basis for multi-dimensional statistic information processing, they constitute the basis for the generalized characteristics of rocks which brings about the solution of classification problem for rocks of different deposits
Analysis of Statistical Methods Currently used in Toxicology Journals.
Na, Jihye; Yang, Hyeri; Bae, SeungJin; Lim, Kyung-Min
2014-09-01
Statistical methods are frequently used in toxicology, yet it is not clear whether the methods employed by the studies are used consistently and conducted based on sound statistical grounds. The purpose of this paper is to describe statistical methods used in top toxicology journals. More specifically, we sampled 30 papers published in 2014 from Toxicology and Applied Pharmacology, Archives of Toxicology, and Toxicological Science and described methodologies used to provide descriptive and inferential statistics. One hundred thirteen endpoints were observed in those 30 papers, and most studies had sample size less than 10, with the median and the mode being 6 and 3 & 6, respectively. Mean (105/113, 93%) was dominantly used to measure central tendency, and standard error of the mean (64/113, 57%) and standard deviation (39/113, 34%) were used to measure dispersion, while few studies provide justifications regarding why the methods being selected. Inferential statistics were frequently conducted (93/113, 82%), with one-way ANOVA being most popular (52/93, 56%), yet few studies conducted either normality or equal variance test. These results suggest that more consistent and appropriate use of statistical method is necessary which may enhance the role of toxicology in public health.
Statistical Analysis of Video Frame Size Distribution Originating from Scalable Video Codec (SVC
Directory of Open Access Journals (Sweden)
Sima Ahmadpour
2017-01-01
Full Text Available Designing an effective and high performance network requires an accurate characterization and modeling of network traffic. The modeling of video frame sizes is normally applied in simulation studies and mathematical analysis and generating streams for testing and compliance purposes. Besides, video traffic assumed as a major source of multimedia traffic in future heterogeneous network. Therefore, the statistical distribution of video data can be used as the inputs for performance modeling of networks. The finding of this paper comprises the theoretical definition of distribution which seems to be relevant to the video trace in terms of its statistical properties and finds the best distribution using both the graphical method and the hypothesis test. The data set used in this article consists of layered video traces generating from Scalable Video Codec (SVC video compression technique of three different movies.
Energy Technology Data Exchange (ETDEWEB)
GREER DA; THIEN MG
2012-01-12
The ability to effectively mix, sample, certify, and deliver consistent batches of High Level Waste (HLW) feed from the Hanford Double Shell Tanks (DST) to the Waste Treatment and Immobilization Plant (WTP) presents a significant mission risk with potential to impact mission length and the quantity of HLW glass produced. DOE's Tank Operations Contractor, Washington River Protection Solutions (WRPS) has previously presented the results of mixing performance in two different sizes of small scale DSTs to support scale up estimates of full scale DST mixing performance. Currently, sufficient sampling of DSTs is one of the largest programmatic risks that could prevent timely delivery of high level waste to the WTP. WRPS has performed small scale mixing and sampling demonstrations to study the ability to sufficiently sample the tanks. The statistical evaluation of the demonstration results which lead to the conclusion that the two scales of small DST are behaving similarly and that full scale performance is predictable will be presented. This work is essential to reduce the risk of requiring a new dedicated feed sampling facility and will guide future optimization work to ensure the waste feed delivery mission will be accomplished successfully. This paper will focus on the analytical data collected from mixing, sampling, and batch transfer testing from the small scale mixing demonstration tanks and how those data are being interpreted to begin to understand the relationship between samples taken prior to transfer and samples from the subsequent batches transferred. An overview of the types of data collected and examples of typical raw data will be provided. The paper will then discuss the processing and manipulation of the data which is necessary to begin evaluating sampling and batch transfer performance. This discussion will also include the evaluation of the analytical measurement capability with regard to the simulant material used in the demonstration tests. The
Bayesian statistics applied to neutron activation data for reactor flux spectrum analysis
International Nuclear Information System (INIS)
Chiesa, Davide; Previtali, Ezio; Sisti, Monica
2014-01-01
Highlights: • Bayesian statistics to analyze the neutron flux spectrum from activation data. • Rigorous statistical approach for accurate evaluation of the neutron flux groups. • Cross section and activation data uncertainties included for the problem solution. • Flexible methodology applied to analyze different nuclear reactor flux spectra. • The results are in good agreement with the MCNP simulations of neutron fluxes. - Abstract: In this paper, we present a statistical method, based on Bayesian statistics, to analyze the neutron flux spectrum from the activation data of different isotopes. The experimental data were acquired during a neutron activation experiment performed at the TRIGA Mark II reactor of Pavia University (Italy) in four irradiation positions characterized by different neutron spectra. In order to evaluate the neutron flux spectrum, subdivided in energy groups, a system of linear equations, containing the group effective cross sections and the activation rate data, has to be solved. However, since the system’s coefficients are experimental data affected by uncertainties, a rigorous statistical approach is fundamental for an accurate evaluation of the neutron flux groups. For this purpose, we applied the Bayesian statistical analysis, that allows to include the uncertainties of the coefficients and the a priori information about the neutron flux. A program for the analysis of Bayesian hierarchical models, based on Markov Chain Monte Carlo (MCMC) simulations, was used to define the problem statistical model and solve it. The first analysis involved the determination of the thermal, resonance-intermediate and fast flux components and the dependence of the results on the Prior distribution choice was investigated to confirm the reliability of the Bayesian analysis. After that, the main resonances of the activation cross sections were analyzed to implement multi-group models with finer energy subdivisions that would allow to determine the
Shape Analysis of HII Regions - I. Statistical Clustering
Campbell-White, Justyn; Froebrich, Dirk; Kume, Alfred
2018-04-01
We present here our shape analysis method for a sample of 76 Galactic HII regions from MAGPIS 1.4 GHz data. The main goal is to determine whether physical properties and initial conditions of massive star cluster formation is linked to the shape of the regions. We outline a systematic procedure for extracting region shapes and perform hierarchical clustering on the shape data. We identified six groups that categorise HII regions by common morphologies. We confirmed the validity of these groupings by bootstrap re-sampling and the ordinance technique multidimensional scaling. We then investigated associations between physical parameters and the assigned groups. Location is mostly independent of group, with a small preference for regions of similar longitudes to share common morphologies. The shapes are homogeneously distributed across Galactocentric distance and latitude. One group contains regions that are all younger than 0.5 Myr and ionised by low- to intermediate-mass sources. Those in another group are all driven by intermediate- to high-mass sources. One group was distinctly separated from the other five and contained regions at the surface brightness detection limit for the survey. We find that our hierarchical procedure is most sensitive to the spatial sampling resolution used, which is determined for each region from its distance. We discuss how these errors can be further quantified and reduced in future work by utilising synthetic observations from numerical simulations of HII regions. We also outline how this shape analysis has further applications to other diffuse astronomical objects.
Comparative performances analysis of neonatal ventilators.
Baldoli, Ilaria; Tognarelli, Selene; Scaramuzzo, Rosa T; Ciantelli, Massimiliano; Cecchi, Francesca; Gentile, Marzia; Sigali, Emilio; Ghirri, Paolo; Boldrini, Antonio; Menciassi, Arianna; Laschi, Cecilia; Cuttano, Armando
2015-02-08
Mechanical ventilation is a therapeutic action for newborns with respiratory diseases but may have side effects. Correct equipment knowledge and training may limit human errors. We aimed to test different neonatal mechanical ventilators' performances by an acquisition module (a commercial pressure sensor plus an isolated chamber and a dedicated software). The differences (ΔP) between peak pressure values and end-expiration pressure were investigated for each ventilator. We focused on discrepancies among measured and imposed pressure data. A statistical analysis was performed. We investigated the measured/imposed ΔP relation. The ΔP do not reveal univocal trends related to ventilation setting parameters and the data distributions were non-Gaussian. Measured ΔP represent a significant parameter in newborns' ventilation, due to the typical small volumes. The investigated ventilators showed different tendencies. Therefore, a deep specific knowledge of the intensive care devices is mandatory for caregivers to correctly exploit their operating principles.
No-Reference Video Quality Assessment Based on Statistical Analysis in 3D-DCT Domain.
Li, Xuelong; Guo, Qun; Lu, Xiaoqiang
2016-05-13
It is an important task to design models for universal no-reference video quality assessment (NR-VQA) in multiple video processing and computer vision applications. However, most existing NR-VQA metrics are designed for specific distortion types which are not often aware in practical applications. A further deficiency is that the spatial and temporal information of videos is hardly considered simultaneously. In this paper, we propose a new NR-VQA metric based on the spatiotemporal natural video statistics (NVS) in 3D discrete cosine transform (3D-DCT) domain. In the proposed method, a set of features are firstly extracted based on the statistical analysis of 3D-DCT coefficients to characterize the spatiotemporal statistics of videos in different views. These features are used to predict the perceived video quality via the efficient linear support vector regression (SVR) model afterwards. The contributions of this paper are: 1) we explore the spatiotemporal statistics of videos in 3DDCT domain which has the inherent spatiotemporal encoding advantage over other widely used 2D transformations; 2) we extract a small set of simple but effective statistical features for video visual quality prediction; 3) the proposed method is universal for multiple types of distortions and robust to different databases. The proposed method is tested on four widely used video databases. Extensive experimental results demonstrate that the proposed method is competitive with the state-of-art NR-VQA metrics and the top-performing FR-VQA and RR-VQA metrics.
European downstream oil industry safety performance. Statistical summary of reported incidents 2009
International Nuclear Information System (INIS)
Burton, A.; Den Haan, K.H.
2010-10-01
The sixteenth such report by CONCAWE, this issue includes statistics on workrelated personal injuries for the European downstream oil industry's own employees as well as contractors for the year 2009. Data were received from 33 companies representing more than 97% of the European refining capacity. Trends over the last sixteen years are highlighted and the data are also compared to similar statistics from related industries. In addition, this report presents the results of the first Process Safety Performance Indicator data gathering exercise amongst the CONCAWE membership.
2010-05-05
...] Guidance for Industry on Documenting Statistical Analysis Programs and Data Files; Availability AGENCY... documenting statistical analyses and data files submitted to the Center for Veterinary Medicine (CVM) for the... on Documenting Statistical Analysis Programs and Data Files; Availability'' giving interested persons...
Statistical Analysis of TTC Students' performance in the ...
African Journals Online (AJOL)
user17
This study aimed at analysing Teacher Training Colleges students‟ .... and equipment, teaching and learning aids, TTC environment, TTC ..... grounds, classrooms, tutors‟ offices, library, reading space and support staff ... science, clean and secure environment that promotes inclusive, equity and equality of education.
Directory of Open Access Journals (Sweden)
N. A. Bazhayev
2017-01-01
Full Text Available We propose a method of information security monitoring for a wireless network segments of low-power devices, "smart house", "Internet of Things". We have carried out the analysis of characteristics of systems based on wireless technologies, resulting from passive surveillance and active polling of devices that make up the network infrastructure. We have considered a number of external signs of unauthorized access to a wireless network by the potential information security malefactor. The model for analysis of information security conditions is based on the identity, quantity, frequency, and time characteristics. Due to the main features of devices providing network infrastructure, estimation of information security state is directed to the analysis of the system normal operation, rather than the search for signatures and anomalies during performance of various kinds of information attacks. An experiment is disclosed that provides obtaining statistical information on the remote wireless devices, where the accumulation of data for decision-making is done by comparing the statistical information service messages from end nodes in passive and active modes. We present experiment results of the information influence on a typical system. The proposed approach to the analysis of network infrastructure statistical data based on naive Bayesian classifier can be used to determine the state of information security.
Conjunction analysis and propositional logic in fMRI data analysis using Bayesian statistics.
Rudert, Thomas; Lohmann, Gabriele
2008-12-01
To evaluate logical expressions over different effects in data analyses using the general linear model (GLM) and to evaluate logical expressions over different posterior probability maps (PPMs). In functional magnetic resonance imaging (fMRI) data analysis, the GLM was applied to estimate unknown regression parameters. Based on the GLM, Bayesian statistics can be used to determine the probability of conjunction, disjunction, implication, or any other arbitrary logical expression over different effects or contrast. For second-level inferences, PPMs from individual sessions or subjects are utilized. These PPMs can be combined to a logical expression and its probability can be computed. The methods proposed in this article are applied to data from a STROOP experiment and the methods are compared to conjunction analysis approaches for test-statistics. The combination of Bayesian statistics with propositional logic provides a new approach for data analyses in fMRI. Two different methods are introduced for propositional logic: the first for analyses using the GLM and the second for common inferences about different probability maps. The methods introduced extend the idea of conjunction analysis to a full propositional logic and adapt it from test-statistics to Bayesian statistics. The new approaches allow inferences that are not possible with known standard methods in fMRI. (c) 2008 Wiley-Liss, Inc.
Statistical Analysis of CMC Constituent and Processing Data
Fornuff, Jonathan
2004-01-01
observed using statistical analysis software. The ultimate purpose of this study is to determine what variations in material processing can lead to the most critical changes in the materials property. The work I have taken part in this summer explores, in general, the key properties needed In this study SiC/SiC composites of varying architectures, utilizing a boron-nitride (BN)
Statistical Analysis of Deflation in Covariance and Resultant Pc Values for AQUA, AURA and TERRA
Hasan, Syed O.
2016-01-01
This presentation will display statistical analysis performed for raw conjunction CDMs received for the EOS Aqua, Aura and Terra satellites within the period of February 2015 through July 2016. The analysis performed indicates a discernable deflation in covariance calculated at the JSpOC after the utilization of the dynamic drag consider parameter was implemented operationally in May 2015. As a result, the overall diminution in the conjunction plane intersection of the primary and secondary objects appears to be leading to reduced probability of collision (Pc) values for these conjunction events. This presentation also displays evidence for this theory with analysis of Pc trending plots using data calculated by the SpaceNav CRMS system.
Statistical analysis of natural disasters and related losses
Pisarenko, VF
2014-01-01
The study of disaster statistics and disaster occurrence is a complicated interdisciplinary field involving the interplay of new theoretical findings from several scientific fields like mathematics, physics, and computer science. Statistical studies on the mode of occurrence of natural disasters largely rely on fundamental findings in the statistics of rare events, which were derived in the 20th century. With regard to natural disasters, it is not so much the fact that the importance of this problem for mankind was recognized during the last third of the 20th century - the myths one encounters in ancient civilizations show that the problem of disasters has always been recognized - rather, it is the fact that mankind now possesses the necessary theoretical and practical tools to effectively study natural disasters, which in turn supports effective, major practical measures to minimize their impact. All the above factors have resulted in considerable progress in natural disaster research. Substantial accrued ma...