Staging Liver Fibrosis with Statistical Observers
Brand, Jonathan Frieman
Chronic liver disease is a worldwide health problem, and hepatic fibrosis (HF) is one of the hallmarks of the disease. Pathology diagnosis of HF is based on textural change in the liver as a lobular collagen network that develops within portal triads. The scale of collagen lobules is characteristically on order of 1mm, which close to the resolution limit of in vivo Gd-enhanced MRI. In this work the methods to collect training and testing images for a Hotelling observer are covered. An observer based on local texture analysis is trained and tested using wet-tissue phantoms. The technique is used to optimize the MRI sequence based on task performance. The final method developed is a two stage model observer to classify fibrotic and healthy tissue in both phantoms and in vivo MRI images. The first stage observer tests for the presence of local texture. Test statistics from the first observer are used to train the second stage observer to globally sample the local observer results. A decision of the disease class is made for an entire MRI image slice using test statistics collected from the second observer. The techniques are tested on wet-tissue phantoms and in vivo clinical patient data.
Glavatskiĭ, A Ia; Guzhovskaia, N V; Lysenko, S N; Kulik, A V
2005-12-01
The authors proposed a possible preoperative diagnostics of the degree of supratentorial brain gliom anaplasia using statistical analysis methods. It relies on a complex examination of 934 patients with I-IV degree anaplasias, which had been treated in the Institute of Neurosurgery from 1990 to 2004. The use of statistical analysis methods for differential diagnostics of the degree of brain gliom anaplasia may optimize a diagnostic algorithm, increase reliability of obtained data and in some cases avoid carrying out irrational operative intrusions. Clinically important signs for the use of statistical analysis methods directed to preoperative diagnostics of brain gliom anaplasia have been defined
Energy Technology Data Exchange (ETDEWEB)
Comnes, G.A.; Belden, T.N.; Kahn, E.P.
1995-02-01
The market for long-term bulk power is becoming increasingly competitive and mature. Given that many privately developed power projects have been or are being developed in the US, it is possible to begin to evaluate the performance of the market by analyzing its revealed prices. Using a consistent method, this paper presents levelized contract prices for a sample of privately developed US generation properties. The sample includes 26 projects with a total capacity of 6,354 MW. Contracts are described in terms of their choice of technology, choice of fuel, treatment of fuel price risk, geographic location, dispatchability, expected dispatch niche, and size. The contract price analysis shows that gas technologies clearly stand out as the most attractive. At an 80% capacity factor, coal projects have an average 20-year levelized price of $0.092/kWh, whereas natural gas combined cycle and/or cogeneration projects have an average price of $0.069/kWh. Within each technology type subsample, however, there is considerable variation. Prices for natural gas combustion turbines and one wind project are also presented. A preliminary statistical analysis is conducted to understand the relationship between price and four categories of explanatory factors including product heterogeneity, geographic heterogeneity, economic and technological change, and other buyer attributes (including avoided costs). Because of residual price variation, we are unable to accept the hypothesis that electricity is a homogeneous product. Instead, the analysis indicates that buyer value still plays an important role in the determination of price for competitively-acquired electricity.
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...
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...
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.
Statistical Methods and Tools for Hanford Staged Feed Tank Sampling
Energy Technology Data Exchange (ETDEWEB)
Fountain, Matthew S. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Brigantic, Robert T. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Peterson, Reid A. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
2013-10-01
This report summarizes work conducted by Pacific Northwest National Laboratory to technically evaluate the current approach to staged feed sampling of high-level waste (HLW) sludge to meet waste acceptance criteria (WAC) for transfer from tank farms to the Hanford Waste Treatment and Immobilization Plant (WTP). The current sampling and analysis approach is detailed in the document titled Initial Data Quality Objectives for WTP Feed Acceptance Criteria, 24590-WTP-RPT-MGT-11-014, Revision 0 (Arakali et al. 2011). The goal of this current work is to evaluate and provide recommendations to support a defensible, technical and statistical basis for the staged feed sampling approach that meets WAC data quality objectives (DQOs).
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 ...
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
Kinsel, Richard P; Liss, Mindy
2007-01-01
The purpose of this retrospective study was to evaluate the effects of implant dimensions, surface treatment, location in the dental arch, numbers of supporting implant abutments, surgical technique, and generally recognized risk factors on the survival of a series of single-stage Straumann dental implants placed into edentulous arches using an immediate loading protocol. Each patient received between 4 and 18 implants in one or both dental arches. Periapical radiographs were obtained over a 2- to 10-year follow-up period to evaluate crestal bone loss following insertion of the definitive metal-ceramic fixed prostheses. Univariate tests for failure rates as a function of age ( or = 60 years), gender, smoking, bone grafting, dental arch, surface type, anterior versus posterior, number of implants per arch, and surgical technique were made using Fisher exact tests. The Cochran-Armitage test for trend was used to evaluate the presence of a linear trend in failure rates regarding implant length and implant diameter. Logistic regression modeling was used to determine which, if any, of the aforementioned factors would predict patient and implant failure. A significance criterion of P = .05 was utilized. Data were collected for 344 single-stage implants placed into 56 edentulous arches (39 maxillae and 17 mandibles) of 43 patients and immediately loaded with a 1-piece provisional fixed prosthesis. A total of 16 implants failed to successfully integrate, for a survival rate of 95.3%. Increased rates of failure were associated with reduced implant length, placement in the posterior region of the jaw, increased implant diameter, and surface treatment. Implant length emerged as the sole significant predictor of implant failure. In this retrospective analysis of 56 consecutively treated edentulous arches with multiple single-stage dental implants loaded immediately, reduced implant length was the sole significant predictor of failure.
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
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....
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
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....
Colorectal cancer stages transcriptome analysis.
Directory of Open Access Journals (Sweden)
Tianyao Huo
Full Text Available Colorectal cancer (CRC is the third most common cancer and the second leading cause of cancer-related deaths in the United States. The purpose of this study was to evaluate the gene expression differences in different stages of CRC. Gene expression data on 433 CRC patient samples were obtained from The Cancer Genome Atlas (TCGA. Gene expression differences were evaluated across CRC stages using linear regression. Genes with p≤0.001 in expression differences were evaluated further in principal component analysis and genes with p≤0.0001 were evaluated further in gene set enrichment analysis. A total of 377 patients with gene expression data in 20,532 genes were included in the final analysis. The numbers of patients in stage I through IV were 59, 147, 116 and 55, respectively. NEK4 gene, which encodes for NIMA related kinase 4, was differentially expressed across the four stages of CRC. The stage I patients had the highest expression of NEK4 genes, while the stage IV patients had the lowest expressions (p = 9*10-6. Ten other genes (RNF34, HIST3H2BB, NUDT6, LRCh4, GLB1L, HIST2H4A, TMEM79, AMIGO2, C20orf135 and SPSB3 had p value of 0.0001 in the differential expression analysis. Principal component analysis indicated that the patients from the 4 clinical stages do not appear to have distinct gene expression pattern. Network-based and pathway-based gene set enrichment analyses showed that these 11 genes map to multiple pathways such as meiotic synapsis and packaging of telomere ends, etc. Ten of these 11 genes were linked to Gene Ontology terms such as nucleosome, DNA packaging complex and protein-DNA interactions. The protein complex-based gene set analysis showed that four genes were involved in H2AX complex II. This study identified a small number of genes that might be associated with clinical stages of CRC. Our analysis was not able to find a molecular basis for the current clinical staging for CRC based on the gene expression patterns.
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 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
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
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.
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.
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
A statistical approach for segregating cognitive task stages from multivariate fMRI BOLD time series
Directory of Open Access Journals (Sweden)
Charmaine eDemanuele
2015-10-01
Full Text Available Multivariate pattern analysis can reveal new information from neuroimaging data to illuminate human cognition and its disturbances. Here, we develop a methodological approach, based on multivariate statistical/machine learning and time series analysis, to discern cognitive processing stages from fMRI blood oxygenation level dependent (BOLD time series. We apply this method to data recorded from a group of healthy adults whilst performing a virtual reality version of the delayed win-shift radial arm maze task. This task has been frequently used to study working memory and decision making in rodents. Using linear classifiers and multivariate test statistics in conjunction with time series bootstraps, we show that different cognitive stages of the task, as defined by the experimenter, namely, the encoding/retrieval, choice, reward and delay stages, can be statistically discriminated from the BOLD time series in brain areas relevant for decision making and working memory. Discrimination of these task stages was significantly reduced during poor behavioral performance in dorsolateral prefrontal cortex (DLPFC, but not in the primary visual cortex (V1. Experimenter-defined dissection of time series into class labels based on task structure was confirmed by an unsupervised, bottom-up approach based on Hidden Markov Models. Furthermore, we show that different groupings of recorded time points into cognitive event classes can be used to test hypotheses about the specific cognitive role of a given brain region during task execution. We found that whilst the DLPFC strongly differentiated between task stages associated with different memory loads, but not between different visual-spatial aspects, the reverse was true for V1. Our methodology illustrates how different aspects of cognitive information processing during one and the same task can be separated and attributed to specific brain regions based on information contained in multivariate patterns of voxel
Meta-analysis of Gaussian individual patient data: Two-stage or not two-stage?
Morris, Tim P; Fisher, David J; Kenward, Michael G; Carpenter, James R
2018-04-30
Quantitative evidence synthesis through meta-analysis is central to evidence-based medicine. For well-documented reasons, the meta-analysis of individual patient data is held in higher regard than aggregate data. With access to individual patient data, the analysis is not restricted to a "two-stage" approach (combining estimates and standard errors) but can estimate parameters of interest by fitting a single model to all of the data, a so-called "one-stage" analysis. There has been debate about the merits of one- and two-stage analysis. Arguments for one-stage analysis have typically noted that a wider range of models can be fitted and overall estimates may be more precise. The two-stage side has emphasised that the models that can be fitted in two stages are sufficient to answer the relevant questions, with less scope for mistakes because there are fewer modelling choices to be made in the two-stage approach. For Gaussian data, we consider the statistical arguments for flexibility and precision in small-sample settings. Regarding flexibility, several of the models that can be fitted only in one stage may not be of serious interest to most meta-analysis practitioners. Regarding precision, we consider fixed- and random-effects meta-analysis and see that, for a model making certain assumptions, the number of stages used to fit this model is irrelevant; the precision will be approximately equal. Meta-analysts should choose modelling assumptions carefully. Sometimes relevant models can only be fitted in one stage. Otherwise, meta-analysts are free to use whichever procedure is most convenient to fit the identified model. © 2018 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.
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.
Stages of tuberculous meningitis: a clinicoradiologic analysis
International Nuclear Information System (INIS)
Sher, K.; Firdaus, A.; Bullo, N.; Kumar, S.; Abbasi, A.
2013-01-01
Objective: To determine the frequencies and percentages of various clinicoradiologic variables of tuberculosis meningitis (TBM) with reference to British Medical Research Council (BMRC) staging of the disease. Study Design: A case series. Place and Duration of Study: Department of Neurology, Jinnah Postgraduate Medical Centre, Karachi, from October 2010 to September 2011. Methodology: The study included 93 adult patients with the diagnosis of tuberculous meningitis (TBM) at the study place. Patients were divided in three groups according to British Medical Research Council (BMRC) staging of TBM. Different clinical and radiological findings were analyzed at different stages of the disease. Data was analyzed using SPSS (Statistical Package of Social Sciences) version 11.0. Results: A majority of patients were found to be in stage-II disease at the time of admission. History of illness at the time of admission was more than 2 weeks in 50% of stage-I patients but around 80% in stage-II and stage-III patients. Neck stiffness was the most commonly reported finding in all stages. Cranial nerve palsies were higher in stage-III (75%) than in stage-II (43%) and in stage-I (24%) patients. Hydrocephalus and basal enhancement was the most frequently reported radiographic abnormalities. Conclusion: Duration of illness and cranial nerve palsies are important variables in the diagnosis of TBM stages and if TBM is suspected, empiric treatment should be started immediately without bacteriologic proof to prevent morbidity and mortality. (author)
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.
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…
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
Sensitivity Analysis in Two-Stage DEA
Directory of Open Access Journals (Sweden)
Athena Forghani
2015-07-01
Full Text Available Data envelopment analysis (DEA is a method for measuring the efficiency of peer decision making units (DMUs which uses a set of inputs to produce a set of outputs. In some cases, DMUs have a two-stage structure, in which the first stage utilizes inputs to produce outputs used as the inputs of the second stage to produce final outputs. One important issue in two-stage DEA is the sensitivity of the results of an analysis to perturbations in the data. The current paper looks into combined model for two-stage DEA and applies the sensitivity analysis to DMUs on the entire frontier. In fact, necessary and sufficient conditions for preserving a DMU's efficiency classiffication are developed when various data changes are applied to all DMUs.
Sensitivity Analysis in Two-Stage DEA
Directory of Open Access Journals (Sweden)
Athena Forghani
2015-12-01
Full Text Available Data envelopment analysis (DEA is a method for measuring the efficiency of peer decision making units (DMUs which uses a set of inputs to produce a set of outputs. In some cases, DMUs have a two-stage structure, in which the first stage utilizes inputs to produce outputs used as the inputs of the second stage to produce final outputs. One important issue in two-stage DEA is the sensitivity of the results of an analysis to perturbations in the data. The current paper looks into combined model for two-stage DEA and applies the sensitivity analysis to DMUs on the entire frontier. In fact, necessary and sufficient conditions for preserving a DMU's efficiency classiffication are developed when various data changes are applied to all DMUs.
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…
Gandikota, Dhanuj; Hadjiiski, Lubomir; Cha, Kenny H.; Chan, Heang-Ping; Caoili, Elaine M.; Cohan, Richard H.; Weizer, Alon; Alva, Ajjai; Paramagul, Chintana; Wei, Jun; Zhou, Chuan
2018-02-01
In bladder cancer, stage T2 is an important threshold in the decision of administering neoadjuvant chemotherapy. Our long-term goal is to develop a quantitative computerized decision support system (CDSS-S) to aid clinicians in accurate staging. In this study, we examined the effect of stage labels of the training samples on modeling such a system. We used a data set of 84 bladder cancers imaged with CT Urography (CTU). At clinical staging prior to treatment, 43 lesions were staged as below stage T2 and 41 were stage T2 or above. After cystectomy and pathological staging that is considered the gold standard, 10 of the lesions were upstaged to stage T2 or above. After correcting the stage labels, 33 lesions were below stage T2, and 51 were stage T2 or above. For the CDSS-S, the lesions were segmented using our AI-CALS method and radiomic features were extracted. We trained a linear discriminant analysis (LDA) classifier with leave-one-case-out cross validation to distinguish between bladder lesions of stage T2 or above and those below stage T2. The CDSS-S was trained and tested with the corrected post-cystectomy labels, and as a comparison, CDSS-S was also trained with understaged pre-treatment labels and tested on lesions with corrected labels. The test AUC for the CDSS-S trained with corrected labels was 0.89 +/- 0.04. For the CDSS-S trained with understaged pre-treatment labels and tested on the lesions with corrected labels, the test AUC was 0.86 +/- 0.04. The likelihood of stage T2 or above for 9 out of the 10 understaged lesions was correctly increased for the CDSS-S trained with corrected labels. The CDSS-S is sensitive to the accuracy of stage labeling. The CDSS-S trained with correct labels shows promise in prediction of the bladder cancer stage.
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...
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.
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.
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
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.
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).
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.
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.
Ensor, Joie; Riley, Richard D.
2016-01-01
Meta‐analysis using individual participant data (IPD) obtains and synthesises the raw, participant‐level data from a set of relevant studies. The IPD approach is becoming an increasingly popular tool as an alternative to traditional aggregate data meta‐analysis, especially as it avoids reliance on published results and provides an opportunity to investigate individual‐level interactions, such as treatment‐effect modifiers. There are two statistical approaches for conducting an IPD meta‐analysis: one‐stage and two‐stage. The one‐stage approach analyses the IPD from all studies simultaneously, for example, in a hierarchical regression model with random effects. The two‐stage approach derives aggregate data (such as effect estimates) in each study separately and then combines these in a traditional meta‐analysis model. There have been numerous comparisons of the one‐stage and two‐stage approaches via theoretical consideration, simulation and empirical examples, yet there remains confusion regarding when each approach should be adopted, and indeed why they may differ. In this tutorial paper, we outline the key statistical methods for one‐stage and two‐stage IPD meta‐analyses, and provide 10 key reasons why they may produce different summary results. We explain that most differences arise because of different modelling assumptions, rather than the choice of one‐stage or two‐stage itself. We illustrate the concepts with recently published IPD meta‐analyses, summarise key statistical software and provide recommendations for future IPD meta‐analyses. © 2016 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd. PMID:27747915
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....
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
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...
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.
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 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.
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
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.
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.
Bun, M.; de Haan, M.
2010-01-01
We analyze the usefulness of the first stage F-statistic for detecting weak instruments in the IV model with a nonscalar error covariance structure. More in particular, we question the validity of the rule of thumb of a first stage F-statistic of 10 or higher for models with correlated errors
Statistical inference for extended or shortened phase II studies based on Simon's two-stage designs.
Zhao, Junjun; Yu, Menggang; Feng, Xi-Ping
2015-06-07
Simon's two-stage designs are popular choices for conducting phase II clinical trials, especially in the oncology trials to reduce the number of patients placed on ineffective experimental therapies. Recently Koyama and Chen (2008) discussed how to conduct proper inference for such studies because they found that inference procedures used with Simon's designs almost always ignore the actual sampling plan used. In particular, they proposed an inference method for studies when the actual second stage sample sizes differ from planned ones. We consider an alternative inference method based on likelihood ratio. In particular, we order permissible sample paths under Simon's two-stage designs using their corresponding conditional likelihood. In this way, we can calculate p-values using the common definition: the probability of obtaining a test statistic value at least as extreme as that observed under the null hypothesis. In addition to providing inference for a couple of scenarios where Koyama and Chen's method can be difficult to apply, the resulting estimate based on our method appears to have certain advantage in terms of inference properties in many numerical simulations. It generally led to smaller biases and narrower confidence intervals while maintaining similar coverages. We also illustrated the two methods in a real data setting. Inference procedures used with Simon's designs almost always ignore the actual sampling plan. Reported P-values, point estimates and confidence intervals for the response rate are not usually adjusted for the design's adaptiveness. Proper statistical inference procedures should be used.
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.
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
Energy Technology Data Exchange (ETDEWEB)
Kawahata, Nobuya; Daitoh, Nobuyuki; Gotoh, Chiharu; Yokoyama, Sakura [Narita Memorial Hospital, Toyohashi, Aichi (Japan)
2001-10-01
One hundred twenty-two patients with dementia of Alzheimer type (DAT) were selected from consecutive referrals to the Memory Clinic at Narita Memorial Hospital. All fulfilled the NINCDS-ADRDA diagnostic criteria for probable Alzheimer's disease. Patients with DAT were subdivided on the results of their score on the Japanese version of Alzheimer's Disease Assessment Scale (ADAS-J cog.), into mild (score lower than or equal to 15, n=47), moderate (score 16 to 35, n=63), and severe (score greater than or equal to 36, n=12) groups. Seventy age-matched controls who had no signs or symptoms of dementia were recruited from the Memory Clinic. The reconstructed {sup 123}I-IMP-SPECT data were analyzed using a statistical parametric mapping technique. In mild stage of DAT, SPM analysis demonstrated that bilateral posterior parietal lobes, superior occipital lobes, and posterior cingulated gyri were significantly decreased in CBF as compared with the normal controls. In moderate stage of DAT, extension of the hypoperfusion to the frontal lobes was detected as compared with the mild stage of DAT. In severe stage of DAT, SPM image showed the diffuse hypoperfusion in bilateral hemispheres. The frequency of hypoperfusions in the DAT group was observed with the following: 15.0% in the mild stage, 34.9% in the moderate stage, and 66.7% in the severe stage. Our results indicate that the frequency and progression of the hypoperfusion in the temporoparietal regions and/or the other regions in DAT is related to the severity of the dementia. (author)
International Nuclear Information System (INIS)
Kawahata, Nobuya; Daitoh, Nobuyuki; Gotoh, Chiharu; Yokoyama, Sakura
2001-01-01
One hundred twenty-two patients with dementia of Alzheimer type (DAT) were selected from consecutive referrals to the Memory Clinic at Narita Memorial Hospital. All fulfilled the NINCDS-ADRDA diagnostic criteria for probable Alzheimer's disease. Patients with DAT were subdivided on the results of their score on the Japanese version of Alzheimer's Disease Assessment Scale (ADAS-J cog.), into mild (score lower than or equal to 15, n=47), moderate (score 16 to 35, n=63), and severe (score greater than or equal to 36, n=12) groups. Seventy age-matched controls who had no signs or symptoms of dementia were recruited from the Memory Clinic. The reconstructed 123 I-IMP-SPECT data were analyzed using a statistical parametric mapping technique. In mild stage of DAT, SPM analysis demonstrated that bilateral posterior parietal lobes, superior occipital lobes, and posterior cingulated gyri were significantly decreased in CBF as compared with the normal controls. In moderate stage of DAT, extension of the hypoperfusion to the frontal lobes was detected as compared with the mild stage of DAT. In severe stage of DAT, SPM image showed the diffuse hypoperfusion in bilateral hemispheres. The frequency of hypoperfusions in the DAT group was observed with the following: 15.0% in the mild stage, 34.9% in the moderate stage, and 66.7% in the severe stage. Our results indicate that the frequency and progression of the hypoperfusion in the temporoparietal regions and/or the other regions in DAT is related to the severity of the dementia. (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.
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).
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.
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...
Structural analysis at aircraft conceptual design stage
Mansouri, Reza
. Considering the strength and limitations of both methodologies, the question to be answered in this thesis is: How valuable and compatible are the classical analytical methods in today's conceptual design environment? And can these methods complement each other? To answer these questions, this thesis investigates the pros and cons of classical analytical structural analysis methods during the conceptual design stage through the following objectives: Illustrate structural design methodology of these methods within the framework of Aerospace Vehicle Design (AVD) lab's design lifecycle. Demonstrate the effectiveness of moment distribution method through four case studies. This will be done by considering and evaluating the strength and limitation of these methods. In order to objectively quantify the limitation and capabilities of the analytical method at the conceptual design stage, each case study becomes more complex than the one before.
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,
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...
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.
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.
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
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 ...
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 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…
Life cycle analysis in preliminary design stages
Agudelo , Lina-Maria; Mejía-Gutiérrez , Ricardo; Nadeau , Jean-Pierre; PAILHES , Jérôme
2014-01-01
International audience; In a design process the product is decomposed into systems along the disciplinary lines. Each stage has its own goals and constraints that must be satisfied and has control over a subset of design variables that describe the overall system. When using different tools to initiate a product life cycle, including the environment and impacts, its noticeable that there is a gap in tools that linked the stages of preliminary design and the stages of materialization. Differen...
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
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.
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.
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.
Market-stage analysis enhances strategic planning.
McDonald, R B
1998-07-01
Changing market conditions are challenging healthcare organizations to determine how to allocate resources and make operational planning decisions to prepare for future changes. A vital part of meeting these challenges is understanding the impact of market stages, and using that knowledge to build effective business strategies. Financial modeling that includes market-stage information provides insight into market opportunities and presents a clearer picture of the organizational changes that will need to be implemented at each stage. Effective strategic action should take into account critical success factors in market responsiveness, organizational responsiveness, operational effectiveness, and financial strength.
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.
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...
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
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 ...
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)
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.
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
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
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.
Erikson Psychosocial Stage Inventory: A Factor Analysis
Gray, Mary McPhail; And Others
1986-01-01
The 72-item Erikson Psychosocial Stage Inventory (EPSI) was factor analyzed for a group of 534 university freshmen and sophomore students. Seven factors emerged, which were labeled Initiative, Industry, Identity, Friendship, Dating, Goal Clarity, and Self-Confidence. Item's representing Erikson's factors, Trust and Autonomy, were dispersed across…
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.
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
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.
International Nuclear Information System (INIS)
Lachet, Bernard.
1975-01-01
A statistical study was carried out on 208 survival curves for chlorella subjected to γ or particle radiations. The computing programmes used were written in Fortran. The different experimental causes contributing to the variance of a survival rate are analyzed and consequently the experiments can be planned. Each curve was fitted to four models by the weighted least squares method applied to non-linear functions. The validity of the fits obtained can be checked by the F test. It was possible to define the confidence and prediction zones around an adjusted curve by weighting of the residual variance, in spite of error on the doses delivered; the confidence limits can them be fixed for a dose estimated from an exact or measured survival. The four models adopted were compared for the precision of their fit (by a non-parametric simultaneous comparison test) and the scattering of their adjusted parameters: Wideroe's model gives a very good fit with the experimental points in return for a scattering of its parameters, which robs them of their presumed meaning. The principal component analysis showed the statistical equivalence of the 1 and 2 hit target models. Division of the irradiation into two doses, the first fixed by the investigator, leads to families of curves for which the equation was established from that of any basic model expressing the dose survival relationship in one-stage irradiation [fr
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.
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.
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)
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
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
International Nuclear Information System (INIS)
Gharehbagheri, Hassan; Safdari, Jaber; Roostaazad, Reza; Rashidi, Abbas
2013-01-01
Highlights: ► In this work, the percent of vanadium recovery from uranium mine waste was 44.8. ► Unlike autotrophs, Aspergillus niger is a suitable microorganism to deal with such a resource. ► In the first step of the present work, citric acid was produced more than the other acids. ► When sterilization of uranium ore waste is not economic, two-step bioleaching is an appropriate method. - Abstract: In this investigation, bioleaching of vanadium from uranium ore residue of the leaching stage was studied by Aspergillus niger in a two-step process at 30 °C and 150 rpm. The first step was initiated by growth of fungi in the absence of mine waste. Using response surface methodology, three factors were surveyed for fungal growth: initial pH, sucrose concentration and spore population. Also concentrations of oxalic, citric, and gluconic acids were measured as response in this step. During 30 days, maximum productions of these acids were 3265, 11578, and 7988 mg/l, respectively. Initial pH and sucrose concentration were significant factors for oxalic and citric acid production; however, for gluconic acid production sucrose concentration and spore population were significant. Then, the content of each flask was filtered and mine waste was added to liquor with pulp density of 3%. During 3 days, in the second step, vanadium recovered about 44.8% in the liquor
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.
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)
A two stage data envelopment analysis model with undesirable output
Shariff Adli Aminuddin, Adam; Izzati Jaini, Nur; Mat Kasim, Maznah; Nawawi, Mohd Kamal Mohd
2017-09-01
The dependent relationship among the decision making units (DMU) is usually assumed to be non-existent in the development of Data Envelopment Analysis (DEA) model. The dependency can be represented by the multi-stage DEA model, where the outputs from the precedent stage will be the inputs for the latter stage. The multi-stage DEA model evaluate both the efficiency score for each stages and the overall efficiency of the whole process. The existing multi stage DEA models do not focus on the integration with the undesirable output, in which the higher input will generate lower output unlike the normal desirable output. This research attempts to address the inclusion of such undesirable output and investigate the theoretical implication and potential application towards the development of multi-stage DEA model.
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.
Using DEWIS and R for Multi-Staged Statistics e-Assessments
Gwynllyw, D. Rhys; Weir, Iain S.; Henderson, Karen L.
2016-01-01
We demonstrate how the DEWIS e-Assessment system may use embedded R code to facilitate the assessment of students' ability to perform involved statistical analyses. The R code has been written to emulate SPSS output and thus the statistical results for each bespoke data set can be generated efficiently and accurately using standard R routines.…
Spatial statistics of magnetic field in two-dimensional chaotic flow in the resistive growth stage
Energy Technology Data Exchange (ETDEWEB)
Kolokolov, I.V., E-mail: igor.kolokolov@gmail.com [Landau Institute for Theoretical Physics RAS, 119334, Kosygina 2, Moscow (Russian Federation); NRU Higher School of Economics, 101000, Myasnitskaya 20, Moscow (Russian Federation)
2017-03-18
The correlation tensors of magnetic field in a two-dimensional chaotic flow of conducting fluid are studied. It is shown that there is a stage of resistive evolution where the field correlators grow exponentially with time. The two- and four-point field correlation tensors are computed explicitly in this stage in the framework of Batchelor–Kraichnan–Kazantsev model. They demonstrate strong temporal intermittency of the field fluctuations and high level of non-Gaussianity in spatial field distribution.
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
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...
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.
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...
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.
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...
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...
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)
Directory of Open Access Journals (Sweden)
Mabaso Musawenkosi LH
2007-09-01
produced a highly plausible and parsimonious model of historical malaria risk for Botswana from point-referenced data from a 1961/2 prevalence survey of malaria infection in 1–14 year old children. After starting with a list of 50 potential variables we ended with three highly plausible predictors, by applying a systematic and repeatable staged variable selection procedure that included a spatial analysis, which has application for other environmentally determined infectious diseases. All this was accomplished using general-purpose statistical software.
Two-stage meta-analysis of survival data from individual participants using percentile ratios
Barrett, Jessica K; Farewell, Vern T; Siannis, Fotios; Tierney, Jayne; Higgins, Julian P T
2012-01-01
Methods for individual participant data meta-analysis of survival outcomes commonly focus on the hazard ratio as a measure of treatment effect. Recently, Siannis et al. (2010, Statistics in Medicine 29:3030–3045) proposed the use of percentile ratios as an alternative to hazard ratios. We describe a novel two-stage method for the meta-analysis of percentile ratios that avoids distributional assumptions at the study level. Copyright © 2012 John Wiley & Sons, Ltd. PMID:22825835
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...
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
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.
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...
Engineering analysis of the two-stage trifluoride precipitation process
International Nuclear Information System (INIS)
Luerkens, D.w.W.
1984-06-01
An engineering analysis of two-stage trifluoride precipitation processes is developed. Precipitation kinetics are modeled using consecutive reactions to represent fluoride complexation. Material balances across the precipitators are used to model the time dependent concentration profiles of the main chemical species. The results of the engineering analysis are correlated with previous experimental work on plutonium trifluoride and cerium trifluoride
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...
Early stage design and analysis of biorefinery networks
DEFF Research Database (Denmark)
Sin, Gürkan
2013-01-01
Recent work regarding biorefineries resulted in many competing concepts and technologies for conversion of renewable bio-based feedstock into many promising products including fuels, chemicals, materials, etc. The design of a biorefinery process requires, at its earlier stages, the selection...... of the process configuration which exhibits the best performances, for a given set of economical, technical and environmental criteria. To this end, we formulate a computer-aided framework as an enabling technology for early stage design and analysis of biorefineries. The tool represents different raw materials......, different products and different available technologies and proposes a conceptual (early stage) biorefinery network. This network can then be the basis for further detailed and rigorous model-based studies. In this talk, we demonstrate the application of the tool for generating an early stage optimal...
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
Statistical geological discrete fracture network model. Forsmark modelling stage 2.2
International Nuclear Information System (INIS)
Fox, Aaron; La Pointe, Paul; Simeonov, Assen; Hermanson, Jan; Oehman, Johan
2007-11-01
The Swedish Nuclear Fuel and Waste Management Company (SKB) is performing site characterization at two different locations, Forsmark and Laxemar, in order to locate a site for a final geologic repository for spent nuclear fuel. The program is built upon the development of Site Descriptive Models (SDMs) at specific timed data freezes. Each SDM is formed from discipline-specific reports from across the scientific spectrum. This report describes the methods, analyses, and conclusions of the geological modeling team with respect to a geological and statistical model of fractures and minor deformation zones (henceforth referred to as the geological DFN), version 2.2, at the Forsmark site. The geological DFN builds upon the work of other geological modelers, including the deformation zone (DZ), rock domain (RD), and fracture domain (FD) models. The geological DFN is a statistical model for stochastically simulating rock fractures and minor deformation zones as a scale of less than 1,000 m (the lower cut-off of the DZ models). The geological DFN is valid within four specific fracture domains inside the local model region, and encompassing the candidate volume at Forsmark: FFM01, FFM02, FFM03, and FFM06. The models are build using data from detailed surface outcrop maps and the cored borehole record at Forsmark. The conceptual model for the Forsmark 2.2 geological revolves around the concept of orientation sets; for each fracture domain, other model parameters such as size and intensity are tied to the orientation sets. Two classes of orientation sets were described; Global sets, which are encountered everywhere in the model region, and Local sets, which represent highly localized stress environments. Orientation sets were described in terms of their general cardinal direction (NE, NW, etc). Two alternatives are presented for fracture size modeling: - the tectonic continuum approach (TCM, TCMF) described by coupled size-intensity scaling following power law distributions
Statistical geological discrete fracture network model. Forsmark modelling stage 2.2
Energy Technology Data Exchange (ETDEWEB)
Fox, Aaron; La Pointe, Paul [Golder Associates Inc (United States); Simeonov, Assen [Swedish Nuclear Fuel and Waste Management Co., Stockholm (Sweden); Hermanson, Jan; Oehman, Johan [Golder Associates AB, Stockholm (Sweden)
2007-11-15
The Swedish Nuclear Fuel and Waste Management Company (SKB) is performing site characterization at two different locations, Forsmark and Laxemar, in order to locate a site for a final geologic repository for spent nuclear fuel. The program is built upon the development of Site Descriptive Models (SDMs) at specific timed data freezes. Each SDM is formed from discipline-specific reports from across the scientific spectrum. This report describes the methods, analyses, and conclusions of the geological modeling team with respect to a geological and statistical model of fractures and minor deformation zones (henceforth referred to as the geological DFN), version 2.2, at the Forsmark site. The geological DFN builds upon the work of other geological modelers, including the deformation zone (DZ), rock domain (RD), and fracture domain (FD) models. The geological DFN is a statistical model for stochastically simulating rock fractures and minor deformation zones as a scale of less than 1,000 m (the lower cut-off of the DZ models). The geological DFN is valid within four specific fracture domains inside the local model region, and encompassing the candidate volume at Forsmark: FFM01, FFM02, FFM03, and FFM06. The models are build using data from detailed surface outcrop maps and the cored borehole record at Forsmark. The conceptual model for the Forsmark 2.2 geological revolves around the concept of orientation sets; for each fracture domain, other model parameters such as size and intensity are tied to the orientation sets. Two classes of orientation sets were described; Global sets, which are encountered everywhere in the model region, and Local sets, which represent highly localized stress environments. Orientation sets were described in terms of their general cardinal direction (NE, NW, etc). Two alternatives are presented for fracture size modeling: - the tectonic continuum approach (TCM, TCMF) described by coupled size-intensity scaling following power law distributions
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.
Second order statistical analysis of US image texture
International Nuclear Information System (INIS)
Tanzi, F.; Novario, R.
1999-01-01
The study reports the sonographic image texture of the neonatal heart in different stages of development by calculating numerical parameters extracted from the gray scale co-occurrence matrix. To show pixel values differences and enhance texture structure, images were equalized and then the gray level range was reduced to 16 to allow sufficiently high occupancy frequency of the co-occurrence matrix. Differences are so little significant that they may be due to different factors affecting image texture and the variability introduced by manual ROI positioning; therefore no definitive conclusions can be drawn as to considering this kind of analysis capable of discriminating different stages of myocardial development [it
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.
Statistical image analysis of cerebral blood flow in moyamoya disease
International Nuclear Information System (INIS)
Yamada, Masaru; Yuzawa, Izumi; Suzuki, Sachio; Kurata, Akira; Fujii, Kiyotaka; Asano, Yuji
2007-01-01
The Summary of this study was to investigate pathophysiology of moyamoya disease, we analyzed brain single photon emission tomography (SPECT) images of patients with this disease by using interface software for a 3-dimensional (3D) data extraction format. Presenting symptoms were transient ischemic attack (TIA) in 21 patients and hemorrhage in 6 patients. All the patients underwent brain SPECT scan of 123 I-iofetamine (IMP) at rest and after acetazolamide challenge (17 mg/kg iv, 2-day method). Cerebral blood flow (CBF) was quantitatively measured using arterial blood sampling and an autoradiography model. The group of the patients who presented with TIAs showed decreased CBF in the frontal lobe at rest compared to that of patients with hemorrhage, but Z-score ((mean-patient data)/ standard deviation (SD)) did not reach statistical significance. Significant CBF decrease after acetazolamide challenge was observed in a wider cerebral cortical area in the TIA group than in the hemorrhagic group. The brain region of hemodynamic ischemia (stage II) correlated well with the responsible cortical area for clinical symptoms of TIA. A hemodynamic ischemia stage image clearly represented recovery of reserve capacity after bypass surgery. Statistical evaluation of SPECT may be useful to understand and clarify the pathophysiology of this disease. (author)
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
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
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)
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.)
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.)
An Analysis of Kohlberg's "Stage 4 1/2" within an Enhanced Framework of Moral Stages.
Minnameier, Gerhard
This paper discusses a well-known problem of stage categorization within Kohlberg's theory of moral stages (L. Kohlberg, 1973), that of "Stage 4 1/2." Some subjects previously scored at stage 4 in Kohlberg's framework took on some characteristics of stage 2 reasoning, which suggested the possibility of regression. To reconcile this…
Acceptance Probability (P a) Analysis for Process Validation Lifecycle Stages.
Alsmeyer, Daniel; Pazhayattil, Ajay; Chen, Shu; Munaretto, Francesco; Hye, Maksuda; Sanghvi, Pradeep
2016-04-01
This paper introduces an innovative statistical approach towards understanding how variation impacts the acceptance criteria of quality attributes. Because of more complex stage-wise acceptance criteria, traditional process capability measures are inadequate for general application in the pharmaceutical industry. The probability of acceptance concept provides a clear measure, derived from specific acceptance criteria for each quality attribute. In line with the 2011 FDA Guidance, this approach systematically evaluates data and scientifically establishes evidence that a process is capable of consistently delivering quality product. The probability of acceptance provides a direct and readily understandable indication of product risk. As with traditional capability indices, the acceptance probability approach assumes that underlying data distributions are normal. The computational solutions for dosage uniformity and dissolution acceptance criteria are readily applicable. For dosage uniformity, the expected AV range may be determined using the s lo and s hi values along with the worst case estimates of the mean. This approach permits a risk-based assessment of future batch performance of the critical quality attributes. The concept is also readily applicable to sterile/non sterile liquid dose products. Quality attributes such as deliverable volume and assay per spray have stage-wise acceptance that can be converted into an acceptance probability. Accepted statistical guidelines indicate processes with C pk > 1.33 as performing well within statistical control and those with C pk 1.33 is associated with a centered process that will statistically produce less than 63 defective units per million. This is equivalent to an acceptance probability of >99.99%.
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
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)
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.
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
Multicriteria analysis of product operational effectiveness at design stages
Irzaev, G. Kh
2018-03-01
The multicriteria rapid assessment method of techno-economic parameters of new products is developed. It avoids expensive engineering changes during the operational stages through the analysis of external and internal factors at an early stage in the design that affect the maintainability and manufacturability of the product. The expert selection of the initial multitude of indicators from the five enlarged criteria groups and their subsequent pairwise comparison allow one to distinguish the complex compliance criteria of product design with the average and optimum values of the operational effectiveness. The values comparison provides an opportunity to decide on the continuation of the process for designing and preparation of the product manufacture.
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.
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
Directory of Open Access Journals (Sweden)
Lange J
2012-03-01
Full Text Available Jeppe Lange1,2, Anders Troelsen3, Reimar W Thomsen4, Kjeld Søballe1,51Lundbeck Foundation Centre for Fast-Track Hip and Knee Surgery, Aarhus C, 2Center for Planned Surgery, Silkeborg Regional Hospital, Silkeborg, 3Department of Orthopaedics, Hvidovre Hospital, Hvidovre, 4Department of Clinical Epidemiology, Aarhus University Hospital, Aalborg, 5Department of Orthopaedics, Aarhus University Hospital, Aarhus C, DenmarkBackground: Two-stage revision is regarded by many as the best treatment of chronic infection in hip arthroplasties. Some international reports, however, have advocated one-stage revision. No systematic review or meta-analysis has ever compared the risk of reinfection following one-stage and two-stage revisions for chronic infection in hip arthroplasties.Methods: The review was performed in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analysis. Relevant studies were identified using PubMed and Embase. We assessed studies that included patients with a chronic infection of a hip arthroplasty treated with either one-stage or two-stage revision and with available data on occurrence of reinfections. We performed a meta-analysis estimating absolute risk of reinfection using a random-effects model.Results: We identified 36 studies eligible for inclusion. None were randomized controlled trials or comparative studies. The patients in these studies had received either one-stage revision (n = 375 or two-stage revision (n = 929. Reinfection occurred with an estimated absolute risk of 13.1% (95% confidence interval: 10.0%–17.1% in the one-stage cohort and 10.4% (95% confidence interval: 8.5%–12.7% in the two-stage cohort. The methodological quality of most included studies was considered low, with insufficient data to evaluate confounding factors.Conclusions: Our results may indicate three additional reinfections per 100 reimplanted patients when performing a one-stage versus two-stage revision. However, the
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.
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.)
A retrospective analysis of preoperative staging modalities for oral squamous cell carcinoma.
Kähling, Ch; Langguth, T; Roller, F; Kroll, T; Krombach, G; Knitschke, M; Streckbein, Ph; Howaldt, H P; Wilbrand, J-F
2016-12-01
An accurate preoperative assessment of cervical lymph node status is a prerequisite for individually tailored cancer therapies in patients with oral squamous cell carcinoma. The detection of malignant spread and its treatment crucially influence the prognosis. The aim of the present study was to analyze the different staging modalities used among patients with a diagnosis of primary oral squamous cell carcinoma between 2008 and 2015. An analysis of preoperative staging findings, collected by clinical palpation, ultrasound, and computed tomography (CT), was performed. The results obtained were compared with the results of the final histopathological findings of the neck dissection specimens. A statistical analysis using McNemar's test was performed. The sensitivity of CT for the detection of malignant cervical tumor spread was 74.5%. The ultrasound obtained a sensitivity of 60.8%. Both CT and ultrasound demonstrated significantly enhanced sensitivity compared to the clinical palpation with a sensitivity of 37.1%. No significant difference was observed between CT and ultrasound. A combination of different staging modalities increased the sensitivity significantly compared with ultrasound staging alone. No significant difference in sensitivity was found between the combined use of different staging modalities and CT staging alone. The highest sensitivity, of 80.0%, was obtained by a combination of all three staging modalities: clinical palpation, ultrasound and CT. The present study indicates that CT has an essential role in the preoperative staging of patients with oral squamous cell carcinoma. Its use not only significantly increases the sensitivity of cervical lymph node metastasis detection but also offers a preoperative assessment of local tumor spread and resection borders. An additional non-invasive cervical lymph node examination increases the sensitivity of the tumor staging process and reduces the risk of occult metastasis. Copyright © 2016 European
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
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
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
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...
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 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.
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
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.
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.
Probability analysis of MCO over-pressurization during staging
International Nuclear Information System (INIS)
Pajunen, A.L.
1997-01-01
The purpose of this calculation is to determine the probability of Multi-Canister Overpacks (MCOs) over-pressurizing during staging at the Canister Storage Building (CSB). Pressurization of an MCO during staging is dependent upon changes to the MCO gas temperature and the build-up of reaction products during the staging period. These effects are predominantly limited by the amount of water that remains in the MCO following cold vacuum drying that is available for reaction during staging conditions. Because of the potential for increased pressure within an MCO, provisions for a filtered pressure relief valve and rupture disk have been incorporated into the MCO design. This calculation provides an estimate of the frequency that an MCO will contain enough water to pressurize beyond the limits of these design features. The results of this calculation will be used in support of further safety analyses and operational planning efforts. Under the bounding steady state CSB condition assumed for this analysis, an MCO must contain less than 1.6 kg (3.7 lbm) of water available for reaction to preclude actuation of the pressure relief valve at 100 psid. To preclude actuation of the MCO rupture disk at 150 psid, an MCO must contain less than 2.5 kg (5.5 lbm) of water available for reaction. These limits are based on the assumption that hydrogen generated by uranium-water reactions is the sole source of gas produced within the MCO and that hydrates in fuel particulate are the primary source of water available for reactions during staging conditions. The results of this analysis conclude that the probability of the hydrate water content of an MCO exceeding 1.6 kg is 0.08 and the probability that it will exceed 2.5 kg is 0.01. This implies that approximately 32 of 400 staged MCOs may experience pressurization to the point where the pressure relief valve actuates. In the event that an MCO pressure relief valve fails to open, the probability is 1 in 100 that the MCO would experience
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.
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
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
Multivariate statistical analysis of a multi-step industrial processes
DEFF Research Database (Denmark)
Reinikainen, S.P.; Høskuldsson, Agnar
2007-01-01
Monitoring and quality control of industrial processes often produce information on how the data have been obtained. In batch processes, for instance, the process is carried out in stages; some process or control parameters are set at each stage. However, the obtained data might not be utilized...... efficiently, even if this information may reveal significant knowledge about process dynamics or ongoing phenomena. When studying the process data, it may be important to analyse the data in the light of the physical or time-wise development of each process step. In this paper, a unified approach to analyse...... multivariate multi-step processes, where results from each step are used to evaluate future results, is presented. The methods presented are based on Priority PLS Regression. The basic idea is to compute the weights in the regression analysis for given steps, but adjust all data by the resulting score vectors...
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.
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
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....
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).
Kittiwisit, Piyanat; Bowman, Judd D.; Jacobs, Daniel C.; Beardsley, Adam P.; Thyagarajan, Nithyanandan
2018-03-01
We present a baseline sensitivity analysis of the Hydrogen Epoch of Reionization Array (HERA) and its build-out stages to one-point statistics (variance, skewness, and kurtosis) of redshifted 21 cm intensity fluctuation from the Epoch of Reionization (EoR) based on realistic mock observations. By developing a full-sky 21 cm light-cone model, taking into account the proper field of view and frequency bandwidth, utilizing a realistic measurement scheme, and assuming perfect foreground removal, we show that HERA will be able to recover statistics of the sky model with high sensitivity by averaging over measurements from multiple fields. All build-out stages will be able to detect variance, while skewness and kurtosis should be detectable for HERA128 and larger. We identify sample variance as the limiting constraint of the measurements at the end of reionization. The sensitivity can also be further improved by performing frequency windowing. In addition, we find that strong sample variance fluctuation in the kurtosis measured from an individual field of observation indicates the presence of outlying cold or hot regions in the underlying fluctuations, a feature that can potentially be used as an EoR bubble indicator.
Vaginal cancer, an analysis of stages 1 and 2
International Nuclear Information System (INIS)
Dickie, G.J.; Tripcony, L.; Otten, G.; Nicklin, J.
2003-01-01
A retrospective analysis was performed of 70 patients with stages 1 and 2 vaginal cancer seen between 1982 and 1998 at the Royal Brisbane and Royal Women's Hospitals, Queensland. Forty three patients had previously had a hysterectomy. Stage, histology and grade were the most important prognostic factors. The 5 year survival rate for stage 1 was 71%, compared to 48% for stage 2. The majority (61 patients) had squamous cell carcinoma with a 68% survival compared to 22% for adenocarcinoma. Those with histological grade 1 and 2 had a 69% survival compared to 40% for grade 3 disease. Age, whether the patient had a previous hysterectomy, tumour site and size were not significant prognostic factors. The majority of patients were treated with radiotherapy alone. However those that had surgery alone or surgery combined with radiotherapy had a significantly improved survival compared to the radiotherapy alone group. The majority of tumours recurred in the loco-regional area and the median time to recurrence was 12 months
Two-Stage Regularized Linear Discriminant Analysis for 2-D Data.
Zhao, Jianhua; Shi, Lei; Zhu, Ji
2015-08-01
Fisher linear discriminant analysis (LDA) involves within-class and between-class covariance matrices. For 2-D data such as images, regularized LDA (RLDA) can improve LDA due to the regularized eigenvalues of the estimated within-class matrix. However, it fails to consider the eigenvectors and the estimated between-class matrix. To improve these two matrices simultaneously, we propose in this paper a new two-stage method for 2-D data, namely a bidirectional LDA (BLDA) in the first stage and the RLDA in the second stage, where both BLDA and RLDA are based on the Fisher criterion that tackles correlation. BLDA performs the LDA under special separable covariance constraints that incorporate the row and column correlations inherent in 2-D data. The main novelty is that we propose a simple but effective statistical test to determine the subspace dimensionality in the first stage. As a result, the first stage reduces the dimensionality substantially while keeping the significant discriminant information in the data. This enables the second stage to perform RLDA in a much lower dimensional subspace, and thus improves the two estimated matrices simultaneously. Experiments on a number of 2-D synthetic and real-world data sets show that BLDA+RLDA outperforms several closely related competitors.
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 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 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
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.
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).
Comparative Proteomic Analysis of Hymenolepis diminuta Cysticercoid and Adult Stages
Directory of Open Access Journals (Sweden)
Anna Sulima
2018-01-01
Full Text Available Cestodiases are common parasitic diseases of animals and humans. As cestodes have complex lifecycles, hexacanth larvae, metacestodes (including cysticercoids, and adults produce proteins allowing them to establish invasion and to survive in the hostile environment of the host. Hymenolepis diminuta is the most commonly used model cestode in experimental parasitology. The aims of the present study were to perform a comparative proteomic analysis of two consecutive developmental stages of H. diminuta (cysticercoid and adult and to distinguish proteins which might be characteristic for each of the stages from those shared by both stages. Somatic proteins of H. diminuta were isolated from 6-week-old cysticercoids and adult tapeworms. Cysticercoids were obtained from experimentally infected beetles, Tenebrio molitor, whereas adult worms were collected from experimentally infected rats. Proteins were separated by GeLC-MS/MS (one dimensional gel electrophoresis coupled with liquid chromatography and tandem mass spectrometry. Additionally protein samples were digested in-liquid and identified by LC-MS/MS. The identified proteins were classified according to molecular function, cellular components and biological processes. Our study showed a number of differences and similarities in the protein profiles of cysticercoids and adults; 233 cysticercoid and 182 adult proteins were identified. From these proteins, 131 were present only in the cysticercoid and 80 only in the adult stage samples. Both developmental stages shared 102 proteins; among which six represented immunomodulators and one is a potential drug target. In-liquid digestion and LC-MS/MS complemented and confirmed some of the GeLC-MS/MS identifications. Possible roles and functions of proteins identified with both proteomic approaches are discussed.
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...
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.
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.
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.
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.
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....
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 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
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
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
Methodology сomparative statistical analysis of Russian industry based on cluster analysis
Directory of Open Access Journals (Sweden)
Sergey S. Shishulin
2017-01-01
Full Text Available The article is devoted to researching of the possibilities of applying multidimensional statistical analysis in the study of industrial production on the basis of comparing its growth rates and structure with other developed and developing countries of the world. The purpose of this article is to determine the optimal set of statistical methods and the results of their application to industrial production data, which would give the best access to the analysis of the result.Data includes such indicators as output, output, gross value added, the number of employed and other indicators of the system of national accounts and operational business statistics. The objects of observation are the industry of the countrys of the Customs Union, the United States, Japan and Erope in 2005-2015. As the research tool used as the simplest methods of transformation, graphical and tabular visualization of data, and methods of statistical analysis. In particular, based on a specialized software package (SPSS, the main components method, discriminant analysis, hierarchical methods of cluster analysis, Ward’s method and k-means were applied.The application of the method of principal components to the initial data makes it possible to substantially and effectively reduce the initial space of industrial production data. Thus, for example, in analyzing the structure of industrial production, the reduction was from fifteen industries to three basic, well-interpreted factors: the relatively extractive industries (with a low degree of processing, high-tech industries and consumer goods (medium-technology sectors. At the same time, as a result of comparison of the results of application of cluster analysis to the initial data and data obtained on the basis of the principal components method, it was established that clustering industrial production data on the basis of new factors significantly improves the results of clustering.As a result of analyzing the parameters of
Cross-View Neuroimage Pattern Analysis for Alzheimer's Disease Staging
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Sidong eLiu
2016-02-01
Full Text Available The research on staging of pre-symptomatic and prodromal phase of neurological disorders, e.g., Alzheimer's disease (AD, is essential for prevention of dementia. New strategies for AD staging with a focus on early detection, are demanded to optimize potential efficacy of disease-modifying therapies that can halt or slow the disease progression. Recently, neuroimaging are increasingly used as additional research-based markers to detect AD onset and predict conversion of MCI and normal control (NC to AD. Researchers have proposed a variety of neuroimaging biomarkers to characterize the patterns of the pathology of AD and MCI, and suggested that multi-view neuroimaging biomarkers could lead to better performance than single-view biomarkers in AD staging. However, it is still unclear what leads to such synergy and how to preserve or maximize. In an attempt to answer these questions, we proposed a cross-view pattern analysis framework for investigating the synergy between different neuroimaging biomarkers. We quantitatively analyzed 9 types of biomarkers derived from FDG-PET and T1-MRI, and evaluated their performance in a task of classifying AD, MCI and NC subjects obtained from the ADNI baseline cohort. The experiment results showed that these biomarkers could depict the pathology of AD from different perspectives, and output distinct patterns that are significantly associated with the disease progression. Most importantly, we found that these features could be separated into clusters, each depicting a particular aspect; and the inter-cluster features could always achieve better performance than the intra-cluster features in AD staging.
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.
Avoiding Pitfalls in the Statistical Analysis of Heterogeneous Tumors
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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.
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
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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
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.
The heat transfer analysis of the first stage blade
International Nuclear Information System (INIS)
Hong, Yong Ju; Choi, Bum Seog; Park, Byung Gyu; Yoon, Eui Soo
2001-01-01
To get higher efficiency of gas turbine, the designer should have more higher Turbine Inlet Temperature(TIT). Today, modern gas turbine having sophisticated cooling scheme has TIT above 1,700 .deg. C. In the Korea, many gas turbine having TIT above 1,300 .deg. C was imported and being operated, but the gas with high TIT above 1,300 .deg. C in the turbine will give damage to liner of combustor, and blade of turbine and etc. So frequently maintenance for parts enduring high temperature was performed. In this study, the heat transfer analysis of cooling air in the internal cooling channel (network analysis) and temperature analysis of the blade (Finite Element Analysis) in the first stage rotor was conducted for development of the optimal cooling passage design procedure. The results of network analysis and FEM analysis of blade show that the high temperature spot are occurred at the leading edge, trailing edge near tip, and platform. So to get more reliable performance of gas turbine, the more efficient cooling method should be applied at the leading edge and tip section and the thermal barrier coating on the blade surface has important role in cooling blade
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
Yinjun Tu; Zhe Zhang; Xudong Gu; Qiang Fang
2016-08-01
Muscle fatigue analysis has been an important topic in sport and rehabilitation medicine due to its role in muscle performance evaluation and pathology investigation. This paper proposes a surface electromyography (sEMG) based muscle fatigue analysis approach which was specifically designed for stroke rehabilitation applications. 14 stroke patients from 5 different Brunnstrom recovery stage groups were involved in the experiment and features including median frequency and mean power frequency were extracted from the collected sEMG samples for investigation. After signal decomposition, the decline of motor unit firing rate of patients from different groups had also been studied. Statistically significant presence of fatigue had been observed in deltoideus medius and extensor digitorum communis of patients at early recovery stages (P0.01). It had also been discovered that the motor unit firing frequency declines with a range positively correlated to the recovery stage during repetitive movements. Based on the experiment result, it can be verified that as the recovery stage increases, the central nervous system's control ability strengthens and the patient motion becomes more stable and resistive to fatigue.
Computerized analysis of fetal heart rate variability signal during the stages of labor.
Annunziata, Maria Laura; Tagliaferri, Salvatore; Esposito, Francesca Giovanna; Giuliano, Natascia; Mereghini, Flavia; Di Lieto, Andrea; Campanile, Marta
2016-03-01
To analyze computerized cardiotocographic (cCTG) parameters (baseline fetal heart rate, baseline FHR; short term variability, STV; approximate entropy, ApEn; low frequency, LF; movement frequency, MF; high frequency, HF) in physiological pregnancy in order to correlate them with the stages of labor. This could provide more information for understanding the mechanisms of nervous system control of FHR during labor progression. A total of 534 pregnant women were monitored on cCTG from the 37th week before the onset of spontaneous labor and during the first and the second stage of labor. Statistical analysis was performed using Kruskal-Wallis test and Wilcoxon rank-sum test with the Bonferroni adjusted α (labor, and the first and second stages of labor. Differences between some of the stages were found for ApEn, LF and for LF/(HF + MF), where the first and the third were reduced and the second was increased. cCTG modifications during labor may reflect the physiologic increased activation of the autonomous nervous system. Using computerized fetal heart rate analysis during labor it may be possible to obtain more information from the fetal cardiac signal, in comparison with the traditional tracing. © 2016 Japan Society of Obstetrics and Gynecology.
Accuracy of the One-Stage and Two-Stage Impression Techniques: A Comparative Analysis.
Jamshidy, Ladan; Mozaffari, Hamid Reza; Faraji, Payam; Sharifi, Roohollah
2016-01-01
Introduction . One of the main steps of impression is the selection and preparation of an appropriate tray. Hence, the present study aimed to analyze and compare the accuracy of one- and two-stage impression techniques. Materials and Methods . A resin laboratory-made model, as the first molar, was prepared by standard method for full crowns with processed preparation finish line of 1 mm depth and convergence angle of 3-4°. Impression was made 20 times with one-stage technique and 20 times with two-stage technique using an appropriate tray. To measure the marginal gap, the distance between the restoration margin and preparation finish line of plaster dies was vertically determined in mid mesial, distal, buccal, and lingual (MDBL) regions by a stereomicroscope using a standard method. Results . The results of independent test showed that the mean value of the marginal gap obtained by one-stage impression technique was higher than that of two-stage impression technique. Further, there was no significant difference between one- and two-stage impression techniques in mid buccal region, but a significant difference was reported between the two impression techniques in MDL regions and in general. Conclusion . The findings of the present study indicated higher accuracy for two-stage impression technique than for the one-stage impression technique.
Accuracy of the One-Stage and Two-Stage Impression Techniques: A Comparative Analysis
Directory of Open Access Journals (Sweden)
Ladan Jamshidy
2016-01-01
Full Text Available Introduction. One of the main steps of impression is the selection and preparation of an appropriate tray. Hence, the present study aimed to analyze and compare the accuracy of one- and two-stage impression techniques. Materials and Methods. A resin laboratory-made model, as the first molar, was prepared by standard method for full crowns with processed preparation finish line of 1 mm depth and convergence angle of 3-4°. Impression was made 20 times with one-stage technique and 20 times with two-stage technique using an appropriate tray. To measure the marginal gap, the distance between the restoration margin and preparation finish line of plaster dies was vertically determined in mid mesial, distal, buccal, and lingual (MDBL regions by a stereomicroscope using a standard method. Results. The results of independent test showed that the mean value of the marginal gap obtained by one-stage impression technique was higher than that of two-stage impression technique. Further, there was no significant difference between one- and two-stage impression techniques in mid buccal region, but a significant difference was reported between the two impression techniques in MDL regions and in general. Conclusion. The findings of the present study indicated higher accuracy for two-stage impression technique than for the one-stage impression technique.
Short-run and Current Analysis Model in Statistics
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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.
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.
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)
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
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)
Transcriptional analysis of late ripening stages of grapevine berry
2011-01-01
Background The composition of grapevine berry at harvest is a major determinant of wine quality. Optimal oenological maturity of berries is characterized by a high sugar/acidity ratio, high anthocyanin content in the skin, and low astringency. However, harvest time is still mostly determined empirically, based on crude biochemical composition and berry tasting. In this context, it is interesting to identify genes that are expressed/repressed specifically at the late stages of ripening and which may be used as indicators of maturity. Results Whole bunches and berries sorted by density were collected in vineyard on Chardonnay (white cultivar) grapevines for two consecutive years at three stages of ripening (7-days before harvest (TH-7), harvest (TH), and 10-days after harvest (TH+10)). Microvinification and sensory analysis indicate that the quality of the wines made from the whole bunches collected at TH-7, TH and TH+10 differed, TH providing the highest quality wines. In parallel, gene expression was studied with Qiagen/Operon microarrays using two types of samples, i.e. whole bunches and berries sorted by density. Only 12 genes were consistently up- or down-regulated in whole bunches and density sorted berries for the two years studied in Chardonnay. 52 genes were differentially expressed between the TH-7 and TH samples. In order to determine whether these genes followed a similar pattern of expression during the late stages of berry ripening in a red cultivar, nine genes were selected for RT-PCR analysis with Cabernet Sauvignon grown under two different temperature regimes affecting the precocity of ripening. The expression profiles and their relationship to ripening were confirmed in Cabernet Sauvignon for seven genes, encoding a carotenoid cleavage dioxygenase, a galactinol synthase, a late embryogenesis abundant protein, a dirigent-like protein, a histidine kinase receptor, a valencene synthase and a putative S-adenosyl-L-methionine:salicylic acid carboxyl
Transcriptional analysis of late ripening stages of grapevine berry
Directory of Open Access Journals (Sweden)
Guillaumie Sabine
2011-11-01
Full Text Available Abstract Background The composition of grapevine berry at harvest is a major determinant of wine quality. Optimal oenological maturity of berries is characterized by a high sugar/acidity ratio, high anthocyanin content in the skin, and low astringency. However, harvest time is still mostly determined empirically, based on crude biochemical composition and berry tasting. In this context, it is interesting to identify genes that are expressed/repressed specifically at the late stages of ripening and which may be used as indicators of maturity. Results Whole bunches and berries sorted by density were collected in vineyard on Chardonnay (white cultivar grapevines for two consecutive years at three stages of ripening (7-days before harvest (TH-7, harvest (TH, and 10-days after harvest (TH+10. Microvinification and sensory analysis indicate that the quality of the wines made from the whole bunches collected at TH-7, TH and TH+10 differed, TH providing the highest quality wines. In parallel, gene expression was studied with Qiagen/Operon microarrays using two types of samples, i.e. whole bunches and berries sorted by density. Only 12 genes were consistently up- or down-regulated in whole bunches and density sorted berries for the two years studied in Chardonnay. 52 genes were differentially expressed between the TH-7 and TH samples. In order to determine whether these genes followed a similar pattern of expression during the late stages of berry ripening in a red cultivar, nine genes were selected for RT-PCR analysis with Cabernet Sauvignon grown under two different temperature regimes affecting the precocity of ripening. The expression profiles and their relationship to ripening were confirmed in Cabernet Sauvignon for seven genes, encoding a carotenoid cleavage dioxygenase, a galactinol synthase, a late embryogenesis abundant protein, a dirigent-like protein, a histidine kinase receptor, a valencene synthase and a putative S
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.
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.
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
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)
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
Data analysis in high energy physics a practical guide to statistical methods
Behnke, Olaf; Kröninger, Kevin; Schott, Grégory; Schörner-Sadenius, Thomas
2013-01-01
This practical guide covers the most essential statistics-related tasks and problems encountered in high-energy physics data analyses. It addresses both advanced students entering the field of particle physics as well as researchers looking for a reliable source on optimal separation of signal and background, determining signals or estimating upper limits, correcting the data for detector effects and evaluating systematic uncertainties. Each chapter is dedicated to a single topic and supplemented by a substantial number of both paper and computer exercises related to real experiments, with the solutions provided at the end of the book along with references. A special feature of the book are the analysis walk-throughs used to illustrate the application of the methods discussed beforehand. The authors give examples of data analysis, referring to real problems in HEP, and display the different stages of data analysis in a descriptive manner. The accompanying website provides more algorithms as well as up-to-date...
Operational statistical analysis of the results of computer-based testing of students
Directory of Open Access Journals (Sweden)
Виктор Иванович Нардюжев
2018-12-01
Full Text Available The article is devoted to the issues of statistical analysis of results of computer-based testing for evaluation of educational achievements of students. The issues are relevant due to the fact that computerbased testing in Russian universities has become an important method for evaluation of educational achievements of students and quality of modern educational process. Usage of modern methods and programs for statistical analysis of results of computer-based testing and assessment of quality of developed tests is an actual problem for every university teacher. The article shows how the authors solve this problem using their own program “StatInfo”. For several years the program has been successfully applied in a credit system of education at such technological stages as loading computerbased testing protocols into a database, formation of queries, generation of reports, lists, and matrices of answers for statistical analysis of quality of test items. Methodology, experience and some results of its usage by university teachers are described in the article. Related topics of a test development, models, algorithms, technologies, and software for large scale computer-based testing has been discussed by the authors in their previous publications which are presented in the reference list.
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
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.
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.
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.
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...
Survival Analysis of Patients with End Stage Renal Disease
Urrutia, J. D.; Gayo, W. S.; Bautista, L. A.; Baccay, E. B.
2015-06-01
This paper provides a survival analysis of End Stage Renal Disease (ESRD) under Kaplan-Meier Estimates and Weibull Distribution. The data were obtained from the records of V. L. MakabaliMemorial Hospital with respect to time t (patient's age), covariates such as developed secondary disease (Pulmonary Congestion and Cardiovascular Disease), gender, and the event of interest: the death of ESRD patients. Survival and hazard rates were estimated using NCSS for Weibull Distribution and SPSS for Kaplan-Meier Estimates. These lead to the same conclusion that hazard rate increases and survival rate decreases of ESRD patient diagnosed with Pulmonary Congestion, Cardiovascular Disease and both diseases with respect to time. It also shows that female patients have a greater risk of death compared to males. The probability risk was given the equation R = 1 — e-H(t) where e-H(t) is the survival function, H(t) the cumulative hazard function which was created using Cox-Regression.
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
Seafloor Topographic Analysis in Staged Ocean Resource Exploration
Ikeda, M.; Okawa, M.; Osawa, K.; Kadoshima, K.; Asakawa, E.; Sumi, T.
2017-12-01
J-MARES (Research and Development Partnership for Next Generation Technology of Marine Resources Survey, JAPAN) has been designing a low-expense and high-efficiency exploration system for seafloor hydrothermal massive sulfide deposits in "Cross-ministerial Strategic Innovation Promotion Program (SIP)" granted by the Cabinet Office, Government of Japan since 2014. We designed a method to focus mineral deposit prospective area in multi-stages (the regional survey, semi-detail survey and detail survey) by extracted topographic features of some well-known seafloor massive sulfide deposits from seafloor topographic analysis using seafloor topographic data acquired by the bathymetric survey. We applied this procedure to an area of interest more than 100km x 100km over Okinawa Trough, including some known seafloor massive sulfide deposits. In Addition, we tried to create a three-dimensional model of seafloor topography by SfM (Structure from Motion) technique using multiple image data of Chimney distributed around well-known seafloor massive sulfide deposit taken with Hi-Vision camera mounted on ROV in detail survey such as geophysical exploration. Topographic features of Chimney was extracted by measuring created three-dimensional model. As the result, it was possible to estimate shape of seafloor sulfide such as Chimney to be mined by three-dimensional model created from image data taken with camera mounted on ROV. In this presentation, we will discuss about focusing mineral deposit prospective area in multi-stages by seafloor topographic analysis using seafloor topographic data in exploration system for seafloor massive sulfide deposit and also discuss about three-dimensional model of seafloor topography created from seafloor image data taken with ROV.
International Nuclear Information System (INIS)
Xu, S.Z.; Wang, L.W.; Wang, R.Z.
2016-01-01
Highlights: • Activated carbon–ammonia multi-stage adsorption refrigerator was analyzed. • COP, exergetic efficiency and entropy production of cycles were calculated. • Single-stage cycle usually has the advantages of simple structure and high COP. • Multi-stage cycles adapt to critical conditions better than single-stage cycle. • Boundary conditions for choosing optimal cycle were summarized as tables. - Abstract: Activated carbon–ammonia multi-stage adsorption refrigeration cycle was analyzed in this article, which realized deep-freezing for evaporating temperature under −18 °C with heating source temperature much lower than 100 °C. Cycle mathematical models for single, two and three-stage cycles were established on the basis of thorough thermodynamic analysis. According to simulation results of thermodynamic evaluation indicators such as COP (coefficient of performance), exergetic efficiency and cycle entropy production, multi-stage cycle adapts to high condensing temperature, low evaporating temperature and low heating source temperature well. Proposed cycle with selected working pair can theoretically work under very severe conditions, such as −25 °C evaporating temperature, 40 °C condensing temperature, and 70 °C heating source temperature, but under these working conditions it has the drawback of low cycle adsorption quantity. It was found that both COP and exergetic efficiency are of great reference value in the choice of cycle, whereas entropy production is not so useful for cycle stage selection. Finally, the application boundary conditions of single-stage, two-stage, and three-stage cycles were summarized as tables according to the simulation results, which provides reference for choosing optimal cycle under different conditions.
Preliminary analysis of Psoroptes ovis transcriptome in different developmental stages
Directory of Open Access Journals (Sweden)
Man-Li He
2016-11-01
Full Text Available Abstract Background Psoroptic mange is a chronic, refractory, contagious and infectious disease mainly caused by the mange mite Psoroptes ovis, which can infect horses, sheep, buffaloes, rabbits, other domestic animals, deer, wild camels, foxes, minks, lemurs, alpacas, elks and other wild animals. Features of the disease include intense pruritus and dermatitis, depilation and hyperkeratosis, which ultimately result in emaciation or death caused by secondary bacterial infections. The infestation is usually transmitted by close contact between animals. Psoroptic mange is widespread in the world. In this paper, the transcriptome of P. ovis is described following sequencing and analysis of transcripts from samples of larvae (i.e. the Pso_L group and nymphs and adults (i.e. the Pso_N_A group. The study describes differentially expressed genes (DEGs and genes encoding allergens, which help understanding the biology of P. ovis and lay foundations for the development of vaccine antigens and drug target screening. Methods The transcriptome of P. ovis was assembled and analyzed using bioinformatic tools. The unigenes of P. ovis from each developmental stage and the unigenes differentially between developmental stages were compared with allergen protein sequences contained in the allergen database website to predict potential allergens. Results We identified 38,836 unigenes, whose mean length was 825 bp. On the basis of sequence similarity with seven databases, a total of 17,366 unigenes were annotated. A total of 1,316 DEGs were identified, including 496 upregulated and 820 downregulated in the Pso_L group compared with the Pso_N_A group. We predicted 205 allergens genes in the two developmental stages similar to genes from other mites and ticks, of these, 14 were among the upregulated DEGs and 26 among the downregulated DEGs. Conclusion This study provides a reference transcriptome of P. ovis in absence of a reference genome. The analysis of DEGs and
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..
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.
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.
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.
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||.
Jiang, H.; Lin, T.
2017-12-01
Rain-fed corn production systems are subject to sub-seasonal variations of precipitation and temperature during the growing season. As each growth phase has varied inherent physiological process, plants necessitate different optimal environmental conditions during each phase. However, this temporal heterogeneity towards climate variability alongside the lifecycle of crops is often simplified and fixed as constant responses in large scale statistical modeling analysis. To capture the time-variant growing requirements in large scale statistical analysis, we develop and compare statistical models at various spatial and temporal resolutions to quantify the relationship between corn yield and weather factors for 12 corn belt states from 1981 to 2016. The study compares three spatial resolutions (county, agricultural district, and state scale) and three temporal resolutions (crop growth phase, monthly, and growing season) to characterize the effects of spatial and temporal variability. Our results show that the agricultural district model together with growth phase resolution can explain 52% variations of corn yield caused by temperature and precipitation variability. It provides a practical model structure balancing the overfitting problem in county specific model and weak explanation power in state specific model. In US corn belt, precipitation has positive impact on corn yield in growing season except for vegetative stage while extreme heat attains highest sensitivity from silking to dough phase. The results show the northern counties in corn belt area are less interfered by extreme heat but are more vulnerable to water deficiency.
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
Statistically based uncertainty assessments in nuclear risk analysis
International Nuclear Information System (INIS)
Spencer, F.W.; Diegert, K.V.; Easterling, R.G.
1987-01-01
Over the last decade, the problems of estimation and uncertainty assessment in probabilistics risk assessment (PRAs) have been addressed in a variety of NRC and industry-sponsored projects. These problems have received attention because of a recognition that major uncertainties in risk estimation exist, which can be reduced by collecting more and better data and other information, and because of a recognition that better methods for assessing these uncertainties are needed. In particular, a clear understanding of the nature and magnitude of various sources of uncertainty is needed to facilitate descision-making on possible plant changes and research options. Recent PRAs have employed methods of probability propagation, sometimes involving the use of Bayes Theorem, and intended to formalize the use of ''engineering judgment'' or ''expert opinion.'' All sources, or feelings, of uncertainty are expressed probabilistically, so that uncertainty analysis becomes simply a matter of probability propagation. Alternatives to forcing a probabilistic framework at all stages of a PRA are a major concern in this paper, however
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
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.
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.
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.)
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.
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
Statistical Analysis of Deep Drilling Process Conditions Using Vibrations and Force Signals
Directory of Open Access Journals (Sweden)
Syafiq Hazwan
2016-01-01
Full Text Available Cooling systems is a key point for hot forming process of Ultra High Strength Steels (UHSS. Normally, cooling systems is made using deep drilling technique. Although deep twist drill is better than other drilling techniques in term of higher productivity however its main problem is premature tool breakage, which affects the production quality. In this paper, analysis of deep twist drill process parameters such as cutting speed, feed rate and depth of cut by using statistical analysis to identify the tool condition is presented. The comparisons between different two tool geometries are also studied. Measured data from vibrations and force sensors are being analyzed through several statistical parameters such as root mean square (RMS, mean, kurtosis, standard deviation and skewness. Result found that kurtosis and skewness value are the most appropriate parameters to represent the deep twist drill tool conditions behaviors from vibrations and forces data. The condition of the deep twist drill process been classified according to good, blunt and fracture. It also found that the different tool geometry parameters affect the performance of the tool drill. It believe the results of this study are useful in determining the suitable analysis method to be used for developing online tool condition monitoring system to identify the tertiary tool life stage and helps to avoid mature of tool fracture during drilling process.
COMBUSTION STAGE NUMERICAL ANALYSIS OF A MARINE ENGINE
Directory of Open Access Journals (Sweden)
DOREL DUMITRU VELCEA
2016-06-01
Full Text Available The primary goal of engine design is to maximize each efficiency factor, in order to extract the most power from the least amount of fuel. In terms of fluid dynamics, the volumetric and combustion efficiency are dependent on the fluid dynamics in the engine manifolds and cylinders. Cold flow analysis involves modeling the airflow in the transient engine cycle without reactions. The goal is to capture the mixture formation process by accurately accounting for the interaction of moving geometry with the fluid dynamics of the induction process. The changing characteristics of the air flow jet that tumbles into the cylinder with swirl via intake valves and the exhaust jet through the exhaust valves as they open and close can be determined, along with the turbulence production from swirl and tumble due to compression and squish. The target of this paper was to show how, by using the reverse engineering techniques, one may replicate and simulate the functioning conditions and parameters of an existing marine engine. The departing information were rather scarce in terms of real processes taking place in the combustion stage, but at the end we managed to have a full picture of the main parameters evolution during the combustion phase inside this existing marine engine
Product analysis of catalytic multi-stage hydropyrolysis of lignite
Energy Technology Data Exchange (ETDEWEB)
Wen Li; Na Wang; Baoqing Li [Chinese Academy of Science, Taiyuan (China). State Key Lab of Coal Conversion, Institute of Coal Chemistry
2003-03-01
A lignite added with 0.2% MoS{sub 2} as catalyst was pyrolyzed under H{sub 2} using multi-stage heating method (MHyPy) which means holding a suitable time near the peak temperature. The product distribution and detailed analysis of products were performed. The results show that the tar yield increased to 63.9% during MHyPy compared with that of 51.8% in traditional hydropyrolysis (HyPy), while the gas yield decreased to a half. This suggests the effective utilization of hydrogen during MHyPy. The light aromatics in the tar from MHyPy increased remarkably 42, 37.8 and 115.4% for BTX, PCX and naphthalenes, respectively. Biphenyls were also observed in the tar from MHyPy, which indicated the effective hydrogenation occurs during catalytic MHyPy. The rich pore structure of the char from MHyPy hints its high reactivity in the subsequent conversion process such as gasification and combustion. 15 refs., 7 figs., 2 tabs.
Energy Technology Data Exchange (ETDEWEB)
Britton, M.D.
1996-10-02
This document provides; a decision analysis summary; problem statement; constraints, requirements, and assumptions; decision criteria; intermediate waste feed staging system options and alternatives generation and screening; intermediate waste feed staging system design concepts; intermediate waste feed staging system alternative evaluation and analysis; and open issues and actions.
Analysis of stage-investing strategy in equity financing market
Institute of Scientific and Technical Information of China (English)
XUN Minghui
2007-01-01
Stage-investing strategy is a primary measure to mitigate asymmetric information during equity investment. This paper attempts to investigate the problem faced by equity investors wishing to make optimal investment decision under stage-investing strategy.A serial investment-decision making model will be designed to help investors to take the best choice.
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.
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…
Directory of Open Access Journals (Sweden)
Korepanov Oleksiy S.
2017-12-01
Full Text Available The aim of the article is to study the labor market in Ukraine in the regional context using cluster analysis methods. The current state of the labor market in regions of Ukraine is analyzed, and a system of statistical indicators that influence the state and development of this market is formed. The expediency of using cluster analysis for grouping regions according to the level of development of the labor market is substantiated. The essence of cluster analysis is revealed, its main goal, key tasks, which can be solved by means of such analysis, are presented, basic stages of the analysis are considered. The main methods of clustering are described and, based on the results of the simulation, the advantages and disadvantages of each method are justified. In the work the clustering of regions of Ukraine by the level of labor market development using different methods of cluster analysis is carried out, conclusions on the results of the calculations performed are presented, and the main directions for further research are outlined.
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
EUS for the staging of gastric cancer: a meta-analysis.
Mocellin, Simone; Marchet, Alberto; Nitti, Donato
2011-06-01
The role of EUS in the locoregional staging of gastric carcinoma is undefined. We aimed to comprehensively review and quantitatively summarize the available evidence on the staging performance of EUS. We systematically searched the MEDLINE, Cochrane, CANCERLIT, and EMBASE databases for relevant studies published until July 2010. Formal meta-analysis of diagnostic accuracy parameters was performed by using a bivariate random-effects model. Fifty-four studies enrolling 5601 patients with gastric cancer undergoing disease staging with EUS were eligible for the meta-analysis. EUS staging accuracy across eligible studies was measured by computing overall sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), and diagnostic odds ratio (DOR). EUS can differentiate T1-2 from T3-4 gastric cancer with high accuracy, with overall sensitivity, specificity, PLR, NLR, and DOR of 0.86 (95% CI, 0.81-0.90), 0.91 (95% CI, 0.89-0.93), 9.8 (95% CI, 7.5-12.8), 0.15 (95% CI, 0.11-0.21), and 65 (95% CI, 41-105), respectively. In contrast, the diagnostic performance of EUS for lymph node status is less reliable, with overall sensitivity, specificity, PLR, NLR, and DOR of 0.69 (95% CI, 0.63-0.74), 0.84 (95% CI, 0.81-0.88), 4.4 (95% CI, 3.6-5.4), 0.37 (95% CI, 0.32-0.44), and 12 (95% CI, 9-16), respectively. Results regarding single T categories (including T1 substages) and Bayesian nomograms to calculate posttest probabilities for any target condition prevalence are also provided. Statistical heterogeneity was generally high; unfortunately, subgroup analysis did not identify a consistent source of the heterogeneity. Our results support the use of EUS for the locoregional staging of gastric cancer, which can affect the therapeutic management of these patients. However, clinicians must be aware of the performance limits of this staging tool. Copyright © 2011 American Society for Gastrointestinal Endoscopy. Published by Mosby, Inc. All rights reserved.
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
Lin, Lung-Chang; Chen, Sharon Chia-Ju; Chiang, Ching-Tai; Wu, Hui-Chuan; Yang, Rei-Cheng; Ouyang, Chen-Sen
2017-03-01
The life quality of patients with refractory epilepsy is extremely affected by abrupt and unpredictable seizures. A reliable method for predicting seizures is important in the management of refractory epilepsy. A critical factor in seizure prediction involves the classification of the preictal and interictal stages. This study aimed to develop an efficient, automatic, quantitative, and individualized approach for preictal/interictal stage identification. Five epileptic children, who had experienced at least 2 episodes of seizures during a 24-hour video EEG recording, were included. Artifact-free preictal and interictal EEG epochs were acquired, respectively, and characterized with 216 global feature descriptors. The best subset of 5 discriminative descriptors was identified. The best subsets showed differences among the patients. Statistical analysis revealed most of the 5 descriptors in each subset were significantly different between the preictal and interictal stages for each patient. The proposed approach yielded weighted averages of 97.50% correctness, 96.92% sensitivity, 97.78% specificity, and 95.45% precision on classifying test epochs. Although the case number was limited, this study successfully integrated a new EEG analytical method to classify preictal and interictal EEG segments and might be used further in predicting the occurrence of seizures.
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.
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...
Analysis of Big Data Maturity Stage in Hospitality Industry
Shabani, Neda; Munir, Arslan; Bose, Avishek
2017-01-01
Big data analytics has an extremely significant impact on many areas in all businesses and industries including hospitality. This study aims to guide information technology (IT) professionals in hospitality on their big data expedition. In particular, the purpose of this study is to identify the maturity stage of the big data in hospitality industry in an objective way so that hotels be able to understand their progress, and realize what it will take to get to the next stage of big data matur...
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 nematode counts from interlaboratory proficiency tests
Berg, van den W.; Hartsema, O.; Nijs, Den J.M.F.
2014-01-01
A series of proficiency tests on potato cyst nematode (PCN; n=29) and free-living stages of Meloidogyne and Pratylenchus (n=23) were investigated to determine the accuracy and precision of the nematode counts and to gain insights into possible trends and potential improvements. In each test, each
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 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...
Statistics and data analysis for financial engineering with R examples
Ruppert, David
2015-01-01
The new edition of this influential textbook, geared towards graduate or advanced undergraduate students, teaches the statistics necessary for financial engineering. In doing so, it illustrates concepts using financial markets and economic data, R Labs with real-data exercises, and graphical and analytic methods for modeling and diagnosing modeling errors. Financial engineers now have access to enormous quantities of data. To make use of these data, the powerful methods in this book, particularly about volatility and risks, are essential. Strengths of this fully-revised edition include major additions to the R code and the advanced topics covered. Individual chapters cover, among other topics, multivariate distributions, copulas, Bayesian computations, risk management, multivariate volatility and cointegration. Suggested prerequisites are basic knowledge of statistics and probability, matrices and linear algebra, and calculus. There is an appendix on probability, statistics and linear algebra. Practicing fina...
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)
Certification of medical librarians, 1949--1977 statistical analysis.
Schmidt, D
1979-01-01
The Medical Library Association's Code for Training and Certification of Medical Librarians was in effect from 1949 to August 1977, a period during which 3,216 individuals were certified. Statistics on each type of certificate granted each year are provided. Because 54.5% of those granted certification were awarded it in the last three-year, two-month period of the code's existence, these applications are reviewed in greater detail. Statistics on each type of certificate granted each year are provided. Because 54.5% of those granted certification were awarded it in the last three-year, two-month period of the code's existence, these applications are reviewed in greater detail. Statistics on MLA membership, sex, residence, library school, and method of meeting requirements are detailed. Questions relating to certification under the code now in existence are raised.
Multivariate Statistical Methods as a Tool of Financial Analysis of Farm Business
Czech Academy of Sciences Publication Activity Database
Novák, J.; Sůvová, H.; Vondráček, Jiří
2002-01-01
Roč. 48, č. 1 (2002), s. 9-12 ISSN 0139-570X Institutional research plan: AV0Z1030915 Keywords : financial analysis * financial ratios * multivariate statistical methods * correlation analysis * discriminant analysis * cluster analysis Subject RIV: BB - Applied Statistics, Operational Research
Performance Analysis of Multi Stage Safety Injection Tank
International Nuclear Information System (INIS)
Shin, Soo Jai; Kim, Young In; Bae, Youngmin; Kang, Han-Ok; Kim, Keung Koo
2015-01-01
In general the integral reactor has such characteristics, the integral reactor requires a high flow rate of coolant safety injection at the initial stage of the accident in which the core level is relatively fast decreased, A medium flow rate of coolant safety injection at the early and middle stages of the accident in which the coolant discharge flow rate is relatively large due to a high internal pressure of the reactor vessel, and a low flow rate of coolant safety injection is required at the middle and late stages of the accident in which the coolant discharge flow rate is greatly reduced due to a decreased pressure of the reactor vessel. It is noted that a high flow rate of the integral reactor is quite smaller compared to a flow rate required in the commercial loop type reactor. However, a nitrogen pressurized safety injection tank has been typically designed to quickly inject a high flow rate of coolant when the internal pressure of the reactor vessel is rapidly decreased, and a core makeup tank has been designed to safely inject at a single mode flow rate due to a gravitational head of water subsequent to making a pressure balance between the reactor vessel and core makeup tank. As a result, in order to compensate such a disadvantage, various type systems are used in a complicated manner in a reactor according to the required characteristic of safety injection during an accident. In the present study, we have investigated numerically the performance of the multi stage safety injection tank. A parameter study has performed to understand the characteristics of the multi stage safety injection tank. The performance of the multi stage safety injection tank has been investigated numerically. When an accident occurs, the coolant in the multi stage safety injection tank is injected into a reactor vessel by a gravitational head of water subsequent to making a pressure balance between the reactor and tank. At the early stages of the accident, the high flow rate of
Performance Analysis of Multi Stage Safety Injection Tank
Energy Technology Data Exchange (ETDEWEB)
Shin, Soo Jai; Kim, Young In; Bae, Youngmin; Kang, Han-Ok; Kim, Keung Koo [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)
2015-10-15
In general the integral reactor has such characteristics, the integral reactor requires a high flow rate of coolant safety injection at the initial stage of the accident in which the core level is relatively fast decreased, A medium flow rate of coolant safety injection at the early and middle stages of the accident in which the coolant discharge flow rate is relatively large due to a high internal pressure of the reactor vessel, and a low flow rate of coolant safety injection is required at the middle and late stages of the accident in which the coolant discharge flow rate is greatly reduced due to a decreased pressure of the reactor vessel. It is noted that a high flow rate of the integral reactor is quite smaller compared to a flow rate required in the commercial loop type reactor. However, a nitrogen pressurized safety injection tank has been typically designed to quickly inject a high flow rate of coolant when the internal pressure of the reactor vessel is rapidly decreased, and a core makeup tank has been designed to safely inject at a single mode flow rate due to a gravitational head of water subsequent to making a pressure balance between the reactor vessel and core makeup tank. As a result, in order to compensate such a disadvantage, various type systems are used in a complicated manner in a reactor according to the required characteristic of safety injection during an accident. In the present study, we have investigated numerically the performance of the multi stage safety injection tank. A parameter study has performed to understand the characteristics of the multi stage safety injection tank. The performance of the multi stage safety injection tank has been investigated numerically. When an accident occurs, the coolant in the multi stage safety injection tank is injected into a reactor vessel by a gravitational head of water subsequent to making a pressure balance between the reactor and tank. At the early stages of the accident, the high flow rate of
Categorical and nonparametric data analysis choosing the best statistical technique
Nussbaum, E Michael
2014-01-01
Featuring in-depth coverage of categorical and nonparametric statistics, this book provides a conceptual framework for choosing the most appropriate type of test in various research scenarios. Class tested at the University of Nevada, the book's clear explanations of the underlying assumptions, computer simulations, and Exploring the Concept boxes help reduce reader anxiety. Problems inspired by actual studies provide meaningful illustrations of the techniques. The underlying assumptions of each test and the factors that impact validity and statistical power are reviewed so readers can explain
Statistical analysis and planning of multihundred-watt impact tests
International Nuclear Information System (INIS)
Martz, H.F. Jr.; Waterman, M.S.
1977-10-01
Modular multihundred-watt (MHW) radioisotope thermoelectric generators (RTG's) are used as a power source for spacecraft. Due to possible environmental contamination by radioactive materials, numerous tests are required to determine and verify the safety of the RTG. There are results available from 27 fueled MHW impact tests regarding hoop failure, fingerprint failure, and fuel failure. Data from the 27 tests are statistically analyzed for relationships that exist between the test design variables and the failure types. Next, these relationships are used to develop a statistical procedure for planning and conducting either future MHW impact tests or similar tests on other RTG fuel sources. Finally, some conclusions are given
Common pitfalls in statistical analysis: The perils of multiple testing
Ranganathan, Priya; Pramesh, C. S.; Buyse, Marc
2016-01-01
Multiple testing refers to situations where a dataset is subjected to statistical testing multiple times - either at multiple time-points or through multiple subgroups or for multiple end-points. This amplifies the probability of a false-positive finding. In this article, we look at the consequences of multiple testing and explore various methods to deal with this issue. PMID:27141478
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 ...
Bayesian statistical analysis of censored data in geotechnical engineering
DEFF Research Database (Denmark)
Ditlevsen, Ove Dalager; Tarp-Johansen, Niels Jacob; Denver, Hans
2000-01-01
The geotechnical engineer is often faced with the problem ofhow to assess the statistical properties of a soil parameter on the basis ofa sample measured in-situ or in the laboratory with the defect that somevalues have been replaced by interval bounds because the corresponding soilparameter values...
Statistical models and NMR analysis of polymer microstructure
Statistical models can be used in conjunction with NMR spectroscopy to study polymer microstructure and polymerization mechanisms. Thus, Bernoullian, Markovian, and enantiomorphic-site models are well known. Many additional models have been formulated over the years for additional situations. Typica...
Toward a theory of statistical tree-shape analysis
DEFF Research Database (Denmark)
Feragen, Aasa; Lo, Pechin Chien Pau; de Bruijne, Marleen
2013-01-01
In order to develop statistical methods for shapes with a tree-structure, we construct a shape space framework for tree-shapes and study metrics on the shape space. This shape space has singularities, which correspond to topological transitions in the represented trees. We study two closely relat...
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.
Statistical analysis of the profile of consumer Internet services
Directory of Open Access Journals (Sweden)
Arzhenovskii Sergei Valentinovich
2014-09-01
Full Text Available Article is devoted to the construction of the Russian Internet user profile. Statistical methods of summary, grouping and the graphical representation of information about Internet consumer by socio-demographic characteristics and settlement are used. RLMS at 2005-2012 years are the information base.
Statistical Analysis of Geo-electric Imaging and Geotechnical Test ...
Indian Academy of Sciences (India)
12
On the other hand cost-effective geoelctric imaging methods provide 2-D / 3-D .... SPSS (Statistical package for social sciences) have been used to carry out linear ..... P W J 1997 Theory of ionic surface electrical conduction in porous media;.
Statistical analysis of the potassium concentration obtained through
International Nuclear Information System (INIS)
Pereira, Joao Eduardo da Silva; Silva, Jose Luiz Silverio da; Pires, Carlos Alberto da Fonseca; Strieder, Adelir Jose
2007-01-01
The present work was developed in outcrops of Santa Maria region, southern Brazil, Rio Grande do Sul State. Statistic evaluations were applied in different rock types. The possibility to distinguish different geologic units, sedimentary and volcanic (acid and basic types) by means of the statistic analyses from the use of airborne gamma-ray spectrometry integrating potash radiation emissions data with geological and geochemistry data is discussed. This Project was carried out at 1973 by Geological Survey of Brazil/Companhia de Pesquisas de Recursos Minerais. The Camaqua Project evaluated the behavior of potash concentrations generating XYZ Geosof 1997 format, one grid, thematic map and digital thematic map files from this total area. Using these data base, the integration of statistics analyses in sedimentary formations which belong to the Depressao Central do Rio Grande do Sul and/or to volcanic rocks from Planalto da Serra Geral at the border of Parana Basin was tested. Univariate statistics model was used: the media, the standard media error, and the trust limits were estimated. The Tukey's Test was used in order to compare mean values. The results allowed to create criteria to distinguish geological formations based on their potash content. The back-calibration technique was employed to transform K radiation to percentage. Inside this context it was possible to define characteristic values from radioactive potash emissions and their trust ranges in relation to geologic formations. The potash variable when evaluated in relation to geographic Universal Transverse Mercator coordinates system showed a spatial relation following one polynomial model of second order, with one determination coefficient. The statistica 7.1 software Generalist Linear Models produced by Statistics Department of Federal University of Santa Maria/Brazil was used. (author)
SIMS analysis using a new novel sample stage
International Nuclear Information System (INIS)
Miwa, Shiro; Nomachi, Ichiro; Kitajima, Hideo
2006-01-01
We have developed a novel sample stage for Cameca IMS-series instruments that allows us to adjust the tilt of the sample holder and to vary the height of the sample surface from outside the vacuum chamber. A third function of the stage is the capability to cool sample to -150 deg. C using liquid nitrogen. Using this stage, we can measure line profiles of 10 mm in length without any variation in the secondary ion yields. By moving the sample surface toward the input lens, the primary ion beam is well focused when the energy of the primary ions is reduced. Sample cooling is useful for samples such as organic materials that are easily damaged by primary ions or electrons
SIMS analysis using a new novel sample stage
Energy Technology Data Exchange (ETDEWEB)
Miwa, Shiro [Materials Analysis Lab., Sony Corporation, 4-16-1 Okata, Atsugi 243-0021 (Japan)]. E-mail: Shiro.Miwa@jp.sony.com; Nomachi, Ichiro [Materials Analysis Lab., Sony Corporation, 4-16-1 Okata, Atsugi 243-0021 (Japan); Kitajima, Hideo [Nanotechnos Corp., 5-4-30 Nishihashimoto, Sagamihara 229-1131 (Japan)
2006-07-30
We have developed a novel sample stage for Cameca IMS-series instruments that allows us to adjust the tilt of the sample holder and to vary the height of the sample surface from outside the vacuum chamber. A third function of the stage is the capability to cool sample to -150 deg. C using liquid nitrogen. Using this stage, we can measure line profiles of 10 mm in length without any variation in the secondary ion yields. By moving the sample surface toward the input lens, the primary ion beam is well focused when the energy of the primary ions is reduced. Sample cooling is useful for samples such as organic materials that are easily damaged by primary ions or electrons.
Critical path analysis in early stage of nuclear power project
International Nuclear Information System (INIS)
Xie Ahai
2009-01-01
The technical program and contract model as well as project management system and preliminary design defined in the early stage of nuclear power project are the key condition impact on the quality, schedule and cost of the nuclear power project. This paper, taking the CPR1000 coastal nuclear power station as an example, analyzes the critical path in the early stage of nuclear power project for five fields, i.e. licensing, design and procurement, site preparation, tender of construction contracts and construction preparation, and organization. (authors)
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...
A Statistical Framework for the Functional Analysis of Metagenomes
Energy Technology Data Exchange (ETDEWEB)
Sharon, Itai; Pati, Amrita; Markowitz, Victor; Pinter, Ron Y.
2008-10-01
Metagenomic studies consider the genetic makeup of microbial communities as a whole, rather than their individual member organisms. The functional and metabolic potential of microbial communities can be analyzed by comparing the relative abundance of gene families in their collective genomic sequences (metagenome) under different conditions. Such comparisons require accurate estimation of gene family frequencies. They present a statistical framework for assessing these frequencies based on the Lander-Waterman theory developed originally for Whole Genome Shotgun (WGS) sequencing projects. They also provide a novel method for assessing the reliability of the estimations which can be used for removing seemingly unreliable measurements. They tested their method on a wide range of datasets, including simulated genomes and real WGS data from sequencing projects of whole genomes. Results suggest that their framework corrects inherent biases in accepted methods and provides a good approximation to the true statistics of gene families in WGS projects.
Common misconceptions about data analysis and statistics1
Motulsky, Harvey J
2015-01-01
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. PMID:25692012
Statistical analysis of field data for aircraft warranties
Lakey, Mary J.
Air Force and Navy maintenance data collection systems were researched to determine their scientific applicability to the warranty process. New and unique algorithms were developed to extract failure distributions which were then used to characterize how selected families of equipment typically fails. Families of similar equipment were identified in terms of function, technology and failure patterns. Statistical analyses and applications such as goodness-of-fit test, maximum likelihood estimation and derivation of confidence intervals for the probability density function parameters were applied to characterize the distributions and their failure patterns. Statistical and reliability theory, with relevance to equipment design and operational failures were also determining factors in characterizing the failure patterns of the equipment families. Inferences about the families with relevance to warranty needs were then made.
STATISTICAL ANALYSYS OF THE SCFE OF A BRAZILAN MINERAL COAL
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DARIVA Cláudio
1997-01-01
Full Text Available The influence of some process variables on the productivity of the fractions (liquid yield times fraction percent obtained from SCFE of a Brazilian mineral coal using isopropanol and ethanol as primary solvents is analyzed using statistical techniques. A full factorial 23 experimental design was adopted to investigate the effects of process variables (temperature, pressure and cosolvent concentration on the extraction products. The extracts were analyzed by the Preparative Liquid Chromatography-8 fractions method (PLC-8, a reliable, non destructive solvent fractionation method, especially developed for coal-derived liquids. Empirical statistical modeling was carried out in order to reproduce the experimental data. Correlations obtained were always greater than 0.98. Four specific process criteria were used to allow process optimization. Results obtained show that it is not possible to maximize both extract productivity and purity (through the minimization of heavy fraction content simultaneously by manipulating the mentioned process variables.
Bogani, Giorgio; Borghi, Chiara; Leone Roberti Maggiore, Umberto; Ditto, Antonino; Signorelli, Mauro; Martinelli, Fabio; Chiappa, Valentina; Lopez, Carlos; Sabatucci, Ilaria; Scaffa, Cono; Indini, Alice; Ferrero, Simone; Lorusso, Domenica; Raspagliesi, Francesco
Few studies investigated the efficacy and safety of minimally invasive surgery for the treatment of early-stage epithelial ovarian cancer (eEOC). In this context, we aimed to review the current evidence comparing laparoscopy and the laparotomic approach for staging procedures in eEOC. This systematic review was registered in the International Prospective Register of Systematic Reviews. Overall, 3065 patients were included: 1450 undergoing laparoscopy and 1615 undergoing laparotomic staging. Patients undergoing laparoscopy experienced a longer (but not statistically significant) operative time (weighted mean difference [WMD] = 28.3 minutes; 95% confidence interval [CI], -2.59 to 59.2), a lower estimated blood loss (WMD = -156.5 mL; 95% CI, -216.4 to -96.5), a shorter length of hospital stay (WMD = -3.7 days; 95% CI, -5.2 to -2.1), and a lower postoperative complication rate (odds ratio [OR] = 0.48; 95% CI, 0.29-0.81) than patients undergoing laparotomy. The upstaging (OR = 0.81; 95% CI, 0.55-1.20) and cyst rupture (OR = 1.32; 95% CI, 0.52-3.38) rates were similar between groups. Laparoscopic staging is associated with a shorter time to chemotherapy than laparotomic procedures (WMD = -5.16 days; 95% CI, -8.68 to -1.64). Survival outcomes were not influenced by the route of surgery. Pooled data suggested that the minimally invasive surgical approach is equivalent to laparotomy for the treatment of eEOC and may be superior in terms of perioperative outcomes. However, because of the low level of evidence of the included studies, further randomized trials are warranted. Copyright © 2017 AAGL. Published by Elsevier Inc. All rights reserved.
STATISTICAL ANALYSIS OF RAW SUGAR MATERIAL FOR SUGAR PRODUCER COMPLEX
A. A. Gromkovskii; O. I. Sherstyuk
2015-01-01
Summary. In the article examines the statistical data on the development of average weight and average sugar content of sugar beet roots. The successful solution of the problem of forecasting these raw indices is essential for solving problems of sugar producing complex control. In the paper by calculating the autocorrelation function demonstrated that the predominant trend component of the growth raw characteristics. For construct the prediction model is proposed to use an autoregressive fir...
Statistical analysis of personal dosimetry of exposed workers
International Nuclear Information System (INIS)
Sanchez Munoz, F. J.; Alejo Luque, L.; Mas Munoz, I.; Serrada Hierro, A.
2013-01-01
The dosimetry centers accredited by the Nuclear Safety Council (CSN) normally report overcoming legal limits, or some fraction thereof, but do not provide comparative dosimetric criteria indicating if assigned to a given dose is large TPE or small relative to that of their peers. In order to help to resolve the difficulties mentioned ds, it has developed an application that statistically processes the dosimetric data provided by the National Dosimetry Center. (Author)
Solar radiation data - statistical analysis and simulation models
Energy Technology Data Exchange (ETDEWEB)
Mustacchi, C; Cena, V; Rocchi, M; Haghigat, F
1984-01-01
The activities consisted in collecting meteorological data on magnetic tape for ten european locations (with latitudes ranging from 42/sup 0/ to 56/sup 0/ N), analysing the multi-year sequences, developing mathematical models to generate synthetic sequences having the same statistical properties of the original data sets, and producing one or more Short Reference Years (SRY's) for each location. The meteorological parameters examinated were (for all the locations) global + diffuse radiation on horizontal surface, dry bulb temperature, sunshine duration. For some of the locations additional parameters were available, namely, global, beam and diffuse radiation on surfaces other than horizontal, wet bulb temperature, wind velocity, cloud type, cloud cover. The statistical properties investigated were mean, variance, autocorrelation, crosscorrelation with selected parameters, probability density function. For all the meteorological parameters, various mathematical models were built: linear regression, stochastic models of the AR and the DAR type. In each case, the model with the best statistical behaviour was selected for the production of a SRY for the relevant parameter/location.
Analysis of multi-stage open shop processing systems
Eggermont, C.E.J.; Schrijver, A.; Woeginger, G.J.; Schwentick, T.; Dürr, C.
2011-01-01
We study algorithmic problems in multi-stage open shop processing systems that are centered around reachability and deadlock detection questions. We characterize safe and unsafe system states. We show that it is easy to recognize system states that can be reached from the initial state (where the
Ramkilowan, A.; Griffith, D. J.
2017-10-01
Surveillance modelling in terms of the standard Detect, Recognise and Identify (DRI) thresholds remains a key requirement for determining the effectiveness of surveillance sensors. With readily available computational resources it has become feasible to perform statistically representative evaluations of the effectiveness of these sensors. A new capability for performing this Monte-Carlo type analysis is demonstrated in the MORTICIA (Monte- Carlo Optical Rendering for Theatre Investigations of Capability under the Influence of the Atmosphere) software package developed at the Council for Scientific and Industrial Research (CSIR). This first generation, python-based open-source integrated software package, currently in the alpha stage of development aims to provide all the functionality required to perform statistical investigations of the effectiveness of optical surveillance systems in specific or generic deployment theatres. This includes modelling of the mathematical and physical processes that govern amongst other components of a surveillance system; a sensor's detector and optical components, a target and its background as well as the intervening atmospheric influences. In this paper we discuss integral aspects of the bespoke framework that are critical to the longevity of all subsequent modelling efforts. Additionally, some preliminary results are presented.
Statistical analysis and data mining of digital reconstructions of dendritic morphologies
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Sridevi ePolavaram
2014-12-01
Full Text Available Neuronal morphology is diverse among animal species, developmental stages, brain regions, and cell types. The geometry of individual neurons also varies substantially even within the same cell class. Moreover, specific histological, imaging, and reconstruction methodologies can differentially affect morphometric measures. The quantitative characterization of neuronal arbors is necessary for in-depth understanding of the structure-function relationship in nervous systems. The large collection of community-contributed digitally reconstructed neurons available at NeuroMorpho.Org constitutes a big data research opportunity for neuroscience discovery beyond the approaches typically pursued in single laboratories. To illustrate these potential and related challenges, we present a database-wide statistical analysis of dendritic arbors enabling the quantification of major morphological similarities and differences across broadly adopted metadata categories. Furthermore, we adopt a complementary unsupervised approach based on clustering and dimensionality reduction to identify the main morphological parameters leading to the most statistically informative structural classification. We find that specific combinations of measures related to branching density, overall size, tortuosity, bifurcation angles, arbor flatness, and topological asymmetry can capture anatomically and functionally relevant features of dendritic trees. The reported results only represent a small fraction of the relationships available for data exploration and hypothesis testing enabled by digital sharing of morphological reconstructions.
Statistical analysis and data mining of digital reconstructions of dendritic morphologies.
Polavaram, Sridevi; Gillette, Todd A; Parekh, Ruchi; Ascoli, Giorgio A
2014-01-01
Neuronal morphology is diverse among animal species, developmental stages, brain regions, and cell types. The geometry of individual neurons also varies substantially even within the same cell class. Moreover, specific histological, imaging, and reconstruction methodologies can differentially affect morphometric measures. The quantitative characterization of neuronal arbors is necessary for in-depth understanding of the structure-function relationship in nervous systems. The large collection of community-contributed digitally reconstructed neurons available at NeuroMorpho.Org constitutes a "big data" research opportunity for neuroscience discovery beyond the approaches typically pursued in single laboratories. To illustrate these potential and related challenges, we present a database-wide statistical analysis of dendritic arbors enabling the quantification of major morphological similarities and differences across broadly adopted metadata categories. Furthermore, we adopt a complementary unsupervised approach based on clustering and dimensionality reduction to identify the main morphological parameters leading to the most statistically informative structural classification. We find that specific combinations of measures related to branching density, overall size, tortuosity, bifurcation angles, arbor flatness, and topological asymmetry can capture anatomically and functionally relevant features of dendritic trees. The reported results only represent a small fraction of the relationships available for data exploration and hypothesis testing enabled by sharing of digital morphological reconstructions.
Shaikh, Masood Ali
2017-09-01
Assessment of research articles in terms of study designs used, statistical tests applied and the use of statistical analysis programmes help determine research activity profile and trends in the country. In this descriptive study, all original articles published by Journal of Pakistan Medical Association (JPMA) and Journal of the College of Physicians and Surgeons Pakistan (JCPSP), in the year 2015 were reviewed in terms of study designs used, application of statistical tests, and the use of statistical analysis programmes. JPMA and JCPSP published 192 and 128 original articles, respectively, in the year 2015. Results of this study indicate that cross-sectional study design, bivariate inferential statistical analysis entailing comparison between two variables/groups, and use of statistical software programme SPSS to be the most common study design, inferential statistical analysis, and statistical analysis software programmes, respectively. These results echo previously published assessment of these two journals for the year 2014.
Normality Tests for Statistical Analysis: A Guide for Non-Statisticians
Ghasemi, Asghar; Zahediasl, Saleh
2012-01-01
Statistical errors are common in scientific literature and about 50% of the published articles have at least one error. The assumption of normality needs to be checked for many statistical procedures, namely parametric tests, because their validity depends on it. The aim of this commentary is to overview checking for normality in statistical analysis using SPSS. PMID:23843808
Radar Derived Spatial Statistics of Summer Rain. Volume 2; Data Reduction and Analysis
Konrad, T. G.; Kropfli, R. A.
1975-01-01
Data reduction and analysis procedures are discussed along with the physical and statistical descriptors used. The statistical modeling techniques are outlined and examples of the derived statistical characterization of rain cells in terms of the several physical descriptors are presented. Recommendations concerning analyses which can be pursued using the data base collected during the experiment are included.
A note on the statistical analysis of point judgment matrices
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MG Kabera
2013-06-01
Full Text Available The Analytic Hierarchy Process is a multicriteria decision making technique developed by Saaty in the 1970s. The core of the approach is the pairwise comparison of objects according to a single criterion using a 9-point ratio scale and the estimation of weights associated with these objects based on the resultant judgment matrix. In the present paper some statistical approaches to extracting the weights of objects from a judgment matrix are reviewed and new ideas which are rooted in the traditional method of paired comparisons are introduced.
Statistical analysis of s-wave neutron reduced widths
International Nuclear Information System (INIS)
Pandita Anita; Agrawal, H.M.
1992-01-01
The fluctuations of the s-wave neutron reduced widths for many nuclei have been analyzed with emphasis on recent measurements by a statistical procedure which is based on the method of maximum likelihood. It is shown that the s-wave neutron reduced widths of nuclei follow single channel Porter Thomas distribution (x 2 -distribution with degree of freedom ν = 1) for most of the cases. However there are apparent deviations from ν = 1 and possible explanation and significance of this deviation is given. These considerations are likely to modify the evaluation of neutron cross section. (author)
Introduction to statistical data analysis for the life sciences
Ekstrom, Claus Thorn
2014-01-01
This text provides a computational toolbox that enables students to analyze real datasets and gain the confidence and skills to undertake more sophisticated analyses. Although accessible with any statistical software, the text encourages a reliance on R. For those new to R, an introduction to the software is available in an appendix. The book also includes end-of-chapter exercises as well as an entire chapter of case exercises that help students apply their knowledge to larger datasets and learn more about approaches specific to the life sciences.
An invariant approach to statistical analysis of shapes
Lele, Subhash R
2001-01-01
INTRODUCTIONA Brief History of MorphometricsFoundations for the Study of Biological FormsDescription of the data SetsMORPHOMETRIC DATATypes of Morphometric DataLandmark Homology and CorrespondenceCollection of Landmark CoordinatesReliability of Landmark Coordinate DataSummarySTATISTICAL MODELS FOR LANDMARK COORDINATE DATAStatistical Models in GeneralModels for Intra-Group VariabilityEffect of Nuisance ParametersInvariance and Elimination of Nuisance ParametersA Definition of FormCoordinate System Free Representation of FormEst
JAWS data collection, analysis highlights, and microburst statistics
Mccarthy, J.; Roberts, R.; Schreiber, W.
1983-01-01
Organization, equipment, and the current status of the Joint Airport Weather Studies project initiated in relation to the microburst phenomenon are summarized. Some data collection techniques and preliminary statistics on microburst events recorded by Doppler radar are discussed as well. Radar studies show that microbursts occur much more often than expected, with majority of the events being potentially dangerous to landing or departing aircraft. Seventy events were registered, with the differential velocities ranging from 10 to 48 m/s; headwind/tailwind velocity differentials over 20 m/s are considered seriously hazardous. It is noted that a correlation is yet to be established between the velocity differential and incoherent radar reflectivity.
Symbolic Data Analysis Conceptual Statistics and Data Mining
Billard, Lynne
2012-01-01
With the advent of computers, very large datasets have become routine. Standard statistical methods don't have the power or flexibility to analyse these efficiently, and extract the required knowledge. An alternative approach is to summarize a large dataset in such a way that the resulting summary dataset is of a manageable size and yet retains as much of the knowledge in the original dataset as possible. One consequence of this is that the data may no longer be formatted as single values, but be represented by lists, intervals, distributions, etc. The summarized data have their own internal s
Process analysis of catalytic multi-stage hydropyrolysis of lignite
Energy Technology Data Exchange (ETDEWEB)
Li, W.; Wang, N.; Li, B. [Chinese Academy of Sciences, Taiyuan (China). Inst. of Coal Chemistry, State Key Laboratory of Coal Conversion
2002-08-01
The process and the mechanism of multi-stage hydropyrolysis (MHyPy) of coal were investigated by analyzing the products of different MHyPy processes in detail. The results showed that the suitable holding temperature was near the peak temperature (350-500{degree}C) at which more free radicals were produced rapidly, thus more oil was formed and the hydrogen utilization efficiency was increased. The cleavage of organic functional groups in char from MHyPy was mostly affected by the pyrolysis temperature. The effect of retention was to change the product distribution through stabilization of the free radicals and hydrogenation of the heavier products. In the holding stage the specific surface area and average pore volume of the char were increased due to the escape of more hydrogenation products. 18 refs., 8 figs., 3 tabs.
Proteomic analysis of the cyst stage of Entamoeba histolytica.
Directory of Open Access Journals (Sweden)
Ibne Karim M Ali
Full Text Available The category B agent of bioterrorism, Entamoeba histolytica has a two-stage life cycle: an infective cyst stage, and an invasive trophozoite stage. Due to our inability to effectively induce encystation in vitro, our knowledge about the cyst form remains limited. This also hampers our ability to develop cyst-specific diagnostic tools.Three main aims were (i to identify E. histolytica proteins in cyst samples, (ii to enrich our knowledge about the cyst stage, and (iii to identify candidate proteins to develop cyst-specific diagnostic tools.Cysts were purified from the stool of infected individuals using Percoll (gradient purification. A highly sensitive LC-MS/MS mass spectrometer (Orbitrap was used to identify cyst proteins.A total of 417 non-redundant E. histolytica proteins were identified including 195 proteins that were never detected in trophozoite-derived proteomes or expressed sequence tag (EST datasets, consistent with cyst specificity. Cyst-wall specific glycoproteins Jacob, Jessie and chitinase were positively identified. Antibodies produced against Jacob identified cysts in fecal specimens and have potential utility as a diagnostic reagent. Several protein kinases, small GTPase signaling molecules, DNA repair proteins, epigenetic regulators, and surface associated proteins were also identified. Proteins we identified are likely to be among the most abundant in excreted cysts, and therefore show promise as diagnostic targets.The proteome data generated here are a first for naturally-occurring E. histolytica cysts, and they provide important insights into the infectious cyst form. Additionally, numerous unique candidate proteins were identified which will aid the development of new diagnostic tools for identification of E. histolytica cysts.
Data analysis of asymmetric structures advanced approaches in computational statistics
Saito, Takayuki
2004-01-01
Data Analysis of Asymmetric Structures provides a comprehensive presentation of a variety of models and theories for the analysis of asymmetry and its applications and provides a wealth of new approaches in every section. It meets both the practical and theoretical needs of research professionals across a wide range of disciplines and considers data analysis in fields such as psychology, sociology, social science, ecology, and marketing. In seven comprehensive chapters this guide details theories, methods, and models for the analysis of asymmetric structures in a variety of disciplines and presents future opportunities and challenges affecting research developments and business applications.
Analysis of interventional therapy for progressing stage gastric cancer
International Nuclear Information System (INIS)
Zhu Mingde; Zhang Zijing; Ji Hongsheng; Ge Chenlin; Hao Gang; Wei Kongming; Yuan Yuhou; Zhao Xiuping
2008-01-01
Objective: To investigate the interventional therapy and its curative effect for progressing stage gastric cancer. Methods: two hundred and twelve patients with progressing stage gastric cancer were treated with arterial perfusion and arterial embolization. Gastric cardia cancer was treated through the left gastric artery and the left inferior phrenic artery or splenic artery. Cancers of lesser and greater gastric curvature was treated either through the left and right gastric arteries or common hepatic artery or through gastroduodenal artery, right gastroomental artery or splenic artery. Gastric antrum cancers were perfused through gastroduodenal artery or after the middle segmental embolization of right gastroomental artery. Results: One hundred and ninety three cases undergone interventional management were followed up. The CR + PR of gastric cardia cancer was 53.13%; gastric body cancer 44.44%; gastric antrum cancer 10%; recurrent cancer and remnant gastric cancer 0. There was no significant difference in outcome between gastric cardia cancer and gastric body cancer (P>0.05) but significant differences were shown both between gastric cardia cancer and gastric antrum cancer, and between gastric body cancer and gastric antrum cancer (P<0.05), with 1 year and 2 years survival rates of 81% and 56% respectively. Conclusion: The interventional therapeutic effect of progressing stage gastric cancers is different due to the different sites of the lesions in the gastric tissue. The curative effect of gastric cardia cancer and gastric body cancer is better than that of gastric antrum cancer, recurrent cancer and remnant gastric cancer. (authors)
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...
Statistical analysis of bankrupting and non-bankrupting stocks
Li, Qian; Wang, Fengzhong; Wei, Jianrong; Liang, Yuan; Huang, Jiping; Stanley, H. Eugene
2012-04-01
The recent financial crisis has caused extensive world-wide economic damage, affecting in particular those who invested in companies that eventually filed for bankruptcy. A better understanding of stocks that become bankrupt would be helpful in reducing risk in future investments. Economists have conducted extensive research on this topic, and here we ask whether statistical physics concepts and approaches may offer insights into pre-bankruptcy stock behavior. To this end, we study all 20092 stocks listed in US stock markets for the 20-year period 1989-2008, including 4223 (21 percent) that became bankrupt during that period. We find that, surprisingly, the distributions of the daily returns of those stocks that become bankrupt differ significantly from those that do not. Moreover, these differences are consistent for the entire period studied. We further study the relation between the distribution of returns and the length of time until bankruptcy, and observe that larger differences of the distribution of returns correlate with shorter time periods preceding bankruptcy. This behavior suggests that sharper fluctuations in the stock price occur when the stock is closer to bankruptcy. We also analyze the cross-correlations between the return and the trading volume, and find that stocks approaching bankruptcy tend to have larger return-volume cross-correlations than stocks that are not. Furthermore, the difference increases as bankruptcy approaches. We conclude that before a firm becomes bankrupt its stock exhibits unusual behavior that is statistically quantifiable.
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
International Nuclear Information System (INIS)
Asano, Yoshitaka; Shinoda, Jun; Okumura, Ayumi; Aki, Tatsuki; Takenaka, Shunsuke; Miwa, Kazuhiro; Yamada, Mikito; Ito, Takeshi; Yokohama, Kazutoshi
2012-01-01
Diffusion tensor imaging (DTI) has recently evolved as valuable technique to investigate diffuse axonal injury (DAI). This study examined whether fractional anisotropy (FA) images analyzed by statistical parametric mapping (FA-SPM images) are superior to T 2 *-weighted gradient recalled echo (T2*GRE) images or fluid-attenuated inversion recovery (FLAIR) images for detecting minute lesions in traumatic brain injury (TBI) patients. DTI was performed in 25 patients with cognitive impairments in the chronic stage after mild or moderate TBI. The FA maps obtained from the DTI were individually compared with those from age-matched healthy control subjects using voxel-based analysis and FA-SPM images (p<0.001). Abnormal low-intensity areas on T2*GRE images (T2* lesions) were found in 10 patients (40.0%), abnormal high-intensity areas on FLAIR images in 4 patients (16.0%), and areas with significantly decreased FA on FA-SPM image in 16 patients (64.0%). Nine of 10 patients with T2* lesions had FA-SPM lesions. FA-SPM lesions topographically included most T2* lesions in the white matter and the deep brain structures, but did not include T2* lesions in the cortex/near-cortex or lesions containing substantial hemosiderin regardless of location. All 4 patients with abnormal areas on FLAIR images had FA-SPM lesions. FA-SPM imaging is useful for detecting minute lesions because of DAI in the white matter and the deep brain structures, which may not be visualized on T2*GRE or FLAIR images, and may allow the detection of minute brain lesions in patients with post-traumatic cognitive impairment. (author)
Statistical analysis of questionnaires a unified approach based on R and Stata
Bartolucci, Francesco; Gnaldi, Michela
2015-01-01
Statistical Analysis of Questionnaires: A Unified Approach Based on R and Stata presents special statistical methods for analyzing data collected by questionnaires. The book takes an applied approach to testing and measurement tasks, mirroring the growing use of statistical methods and software in education, psychology, sociology, and other fields. It is suitable for graduate students in applied statistics and psychometrics and practitioners in education, health, and marketing.The book covers the foundations of classical test theory (CTT), test reliability, va
Energy Technology Data Exchange (ETDEWEB)
Sundberg, Jan; Wrafter, John; Laendell, Maerta (Geo Innova AB (Sweden)); Back, Paer-Erik; Rosen, Lars (Sweco AB (Sweden))
2008-11-15
This report present the results of thermal modelling work for the Forsmark area carried out during modelling stage 2.3. The work complements the main modelling efforts carried out during modelling stage 2.2. A revised spatial statistical description of the rock mass thermal conductivity for rock domain RFM045 is the main result of this work. Thermal modelling of domain RFM045 in Forsmark model stage 2.2 gave lower tail percentiles of thermal conductivity that were considered to be conservatively low due to the way amphibolite, the rock type with the lowest thermal conductivity, was modelled. New and previously available borehole data are used as the basis for revised stochastic geological simulations of domain RFM045. By defining two distinct thermal subdomains, these simulations have succeeded in capturing more of the lithological heterogeneity present. The resulting thermal model for rock domain RFM045 is, therefore, considered to be more realistic and reliable than that presented in model stage 2.2. The main conclusions of modelling efforts in model stage 2.3 are: - Thermal modelling indicates a mean thermal conductivity for domain RFM045 at the 5 m scale of 3.56 W/(mK). This is slightly higher than the value of 3.49 W/(mK) derived in model stage 2.2. - The variance decreases and the lower tail percentiles increase as the scale of observation increases from 1 to 5 m. Best estimates of the 0.1 percentile of thermal conductivity for domain RFM045 are 2.24 W/(mK) for the 1 m scale and 2.36 W/(mK) for the 5 m scale. This can be compared with corresponding values for domain RFM029 of 2.30 W/(mK) for the 1 m scale and 2.87 W/(mK)for the 5 m scale. - The reason for the pronounced lower tail in the thermal conductivity distribution for domain RFM045 is the presence of large bodies of the low-conductive amphibolite. - The modelling results for domain RFM029 presented in model stage 2.2 are still applicable. - As temperature increases, the thermal conductivity decreases
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 mechanics analysis of LDPC coding in MIMO Gaussian channels
Energy Technology Data Exchange (ETDEWEB)
Alamino, Roberto C; Saad, David [Neural Computing Research Group, Aston University, Birmingham B4 7ET (United Kingdom)
2007-10-12
Using analytical methods of statistical mechanics, we analyse the typical behaviour of a multiple-input multiple-output (MIMO) Gaussian channel with binary inputs under low-density parity-check (LDPC) network coding and joint decoding. The saddle point equations for the replica symmetric solution are found in particular realizations of this channel, including a small and large number of transmitters and receivers. In particular, we examine the cases of a single transmitter, a single receiver and symmetric and asymmetric interference. Both dynamical and thermodynamical transitions from the ferromagnetic solution of perfect decoding to a non-ferromagnetic solution are identified for the cases considered, marking the practical and theoretical limits of the system under the current coding scheme. Numerical results are provided, showing the typical level of improvement/deterioration achieved with respect to the single transmitter/receiver result, for the various cases.
Statistical mechanics analysis of LDPC coding in MIMO Gaussian channels
International Nuclear Information System (INIS)
Alamino, Roberto C; Saad, David
2007-01-01
Using analytical methods of statistical mechanics, we analyse the typical behaviour of a multiple-input multiple-output (MIMO) Gaussian channel with binary inputs under low-density parity-check (LDPC) network coding and joint decoding. The saddle point equations for the replica symmetric solution are found in particular realizations of this channel, including a small and large number of transmitters and receivers. In particular, we examine the cases of a single transmitter, a single receiver and symmetric and asymmetric interference. Both dynamical and thermodynamical transitions from the ferromagnetic solution of perfect decoding to a non-ferromagnetic solution are identified for the cases considered, marking the practical and theoretical limits of the system under the current coding scheme. Numerical results are provided, showing the typical level of improvement/deterioration achieved with respect to the single transmitter/receiver result, for the various cases
Statistical Analysis of a Comprehensive List of Visual Binaries
Directory of Open Access Journals (Sweden)
Kovaleva D.
2015-12-01
Full Text Available Visual binary stars are the most abundant class of observed binaries. The most comprehensive list of data on visual binaries compiled recently by cross-matching the largest catalogues of visual binaries allowed a statistical investigation of observational parameters of these systems. The dataset was cleaned by correcting uncertainties and misclassifications, and supplemented with available parallax data. The refined dataset is free from technical biases and contains 3676 presumably physical visual pairs of luminosity class V with known angular separations, magnitudes of the components, spectral types, and parallaxes. We also compiled a restricted sample of 998 pairs free from observational biases due to the probability of binary discovery. Certain distributions of observational and physical parameters of stars of our dataset are discussed.
Statistical analysis of P-wave neutron reduced widths
International Nuclear Information System (INIS)
Joshi, G.C.; Agrawal, H.M.
2000-01-01
The fluctuations of the p-wave neutron reduced widths for fifty one nuclei have been analyzed with emphasis on recent measurements by a statistical procedure which is based on the method of maximum likelihood. It is shown that the p-wave neutron reduced widths of even-even nuclei fallow single channel Porter Thomas distribution (χ 2 -distribution with degree of freedom ν=1) for most of the cases where there are no intermediate structure. It is emphasized that the distribution in nuclei other than even-even may differ from a χ 2 -distribution with one degree of freedom. Possible explanation and significance of this deviation from ν=1 is given. (author)
Statistical analysis of complex systems with nonclassical invariant measures
Fratalocchi, Andrea
2011-02-28
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 general formalism based on the Ablowitz-Kaup-Newell-Segur scheme, I demonstrate how to build an invariant measure and, within a one-dimensional phase space, how to develop a suitable thermodynamics. A detailed example is provided with a universal model of wave propagation, with reference to a transparent potential sustaining gray solitons. The system shows a rich thermodynamic scenario, with a free-energy landscape supporting phase transitions and controllable emergent properties. I finally discuss the origin of such behavior, trying to identify common denominators in the area of complex dynamics.
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 analysis of environmental dose data for Trombay environment
International Nuclear Information System (INIS)
Kale, M.S.; Padmanabhan, N.; Rekha Kutty, R.; Sharma, D.N.; Iyengar, T.S.; Iyer, M.R.
1993-01-01
The microprocessor based environmental dose logging system is functioning at six stations at Trombay for the past couple of years. The site emergency control centre (SECC) at modular laboratory receives telemetered data every five minutes from main guard house (South Site), Bhabha point (top of the hill), Cirus reactor, Mod Lab terrace, Hall No. 7 and Training School Hostel. The data collected are being stored in dbase III + format for easy processing in a PC. Various statistical parameters and distributions of environmental gamma dose are determined from the hourly dose data. On the basis of the reactor operation status an attempt has been made to separate the natural background and the gamma dose contribution due to the operating research reactors in each one of these monitoring stations. Similar investigations are being carried out for Tarapur environment. (author). 2 refs., 3 tabs., 2 figs
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.
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
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...
Lifetime statistics of quantum chaos studied by a multiscale analysis
Di Falco, A.; Krauss, T. F.; Fratalocchi, Andrea
2012-01-01
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
International Nuclear Information System (INIS)
Nakanishi, Hirotaka
1998-01-01
To clarify the utility of the CT image to a clinical diagnosis of the early stage emphysema, the relation of CT value to the level of the lung destruction, the change in the lung density and pulmonary function was examined. Experimental pulmonary emphysema model in canine was produced by inhalation of aerosolized papain solution. In this model, the relationship between the destruction in lung tissues and the analysis of CT images was investigated. Changes in the alveolar surface area per unit lung volume well reflected those in mean CT value in the lung parenchyma. Also, it was clarified that the degree of the lung destruction in this model corresponded to that in patients with the early stage emphysema. Mean CT value in the area that formed lowest 5th percentile of the CT value histogram (mCT (5%ile)) was developed to analyze CT images in emphysema. To develop this study, changes of the mCT (5%ile) at the respiratory level from 5% to 95% inspiratory vital capacity (mCT (5%ile (5-95%VC))) was examined. In experimental studies, there was statistical significance between control and emphysema model. In clinical study using 14 patients with emphysema, the mCT (5%ile (5-95%VC)) reflected well the values of pulmonary function tests which indicated air flow limitation such as %pred. FEV 1.0 and MMF. The present studies demonstrated that it might be useful to detect the pathological and functional impairment in the early stage emphysema by using mCT (5%ile (5-95%VC)). (author)
Statistical analysis of archeomagnetic samples of Teotihuacan, Mexico
Soler-Arechalde, A. M.
2012-12-01
Teotihuacan was the one of the most important metropolis of Mesoamerica during the Classic Period (1 to 600 AC). The city had a continuous growth in different stages that usually concluded with a ritual. Fire was an important element natives would burn entire structures. An example of this is the Quetzalcoatl pyramid in La Ciudadela (350 AC), it was burned and a new structure was built over it, also the Big Fire at 570 AC, that marks its end. These events are suitable to archaeomagnetic dating. The inclusion of ash in the stucco enhances the magnetic signal of detrital type that also allows us to make dating. This increases the number of samples to be processed as well as the number of dates. The samples have been analyzed according to their type: floor, wall, talud and painting and whether or not exposed to fire. Sequences of directions obtained in excavations in strict stratigraphic control will be shown. A sequence of images was used to analyze the improving of Teotihuacan secular variation curve through more than a decade of continuous work at the area.
Research and Development of Statistical Analysis Software System of Maize Seedling Experiment
Hui Cao
2014-01-01
In this study, software engineer measures were used to develop a set of software system for maize seedling experiments statistics and analysis works. During development works, B/S structure software design method was used and a set of statistics indicators for maize seedling evaluation were established. The experiments results indicated that this set of software system could finish quality statistics and analysis for maize seedling very well. The development of this software system explored a...
Power flow as a complement to statistical energy analysis and finite element analysis
Cuschieri, J. M.
1987-01-01
Present methods of analysis of the structural response and the structure-borne transmission of vibrational energy use either finite element (FE) techniques or statistical energy analysis (SEA) methods. The FE methods are a very useful tool at low frequencies where the number of resonances involved in the analysis is rather small. On the other hand SEA methods can predict with acceptable accuracy the response and energy transmission between coupled structures at relatively high frequencies where the structural modal density is high and a statistical approach is the appropriate solution. In the mid-frequency range, a relatively large number of resonances exist which make finite element method too costly. On the other hand SEA methods can only predict an average level form. In this mid-frequency range a possible alternative is to use power flow techniques, where the input and flow of vibrational energy to excited and coupled structural components can be expressed in terms of input and transfer mobilities. This power flow technique can be extended from low to high frequencies and this can be integrated with established FE models at low frequencies and SEA models at high frequencies to form a verification of the method. This method of structural analysis using power flo and mobility methods, and its integration with SEA and FE analysis is applied to the case of two thin beams joined together at right angles.
Statistics Education Research in Malaysia and the Philippines: A Comparative Analysis
Reston, Enriqueta; Krishnan, Saras; Idris, Noraini
2014-01-01
This paper presents a comparative analysis of statistics education research in Malaysia and the Philippines by modes of dissemination, research areas, and trends. An electronic search for published research papers in the area of statistics education from 2000-2012 yielded 20 for Malaysia and 19 for the Philippines. Analysis of these papers showed…
Statistical analysis of correlated experimental data and neutron cross section evaluation
International Nuclear Information System (INIS)
Badikov, S.A.
1998-01-01
The technique for evaluation of neutron cross sections on the basis of statistical analysis of correlated experimental data is presented. The most important stages of evaluation beginning from compilation of correlation matrix for measurement uncertainties till representation of the analysis results in the ENDF-6 format are described in details. Special attention is paid to restrictions (positive uncertainty) on covariation matrix of approximate parameters uncertainties generated within the method of least square fit which is derived from physical reasons. The requirements for source experimental data assuring satisfaction of the restrictions mentioned above are formulated. Correlation matrices of measurement uncertainties in particular should be also positively determined. Variants of modelling the positively determined correlation matrices of measurement uncertainties in a situation when their consequent calculation on the basis of experimental information is impossible are discussed. The technique described is used for creating the new generation of estimates of dosimetric reactions cross sections for the first version of the Russian dosimetric file (including nontrivial covariation information)
Statistical analysis of solar radiation on variously oriented sloping surfaces
International Nuclear Information System (INIS)
Garg, H.P.; Garg, S.N.
1985-12-01
For four years, daily global radiation on a south facing surface and on four vertical walls namely south wall, north wall, east wall and west wall, has been computed and statistically analysed for each of the 4 stations: New Delhi, Calcutta, Poona and Madras. Daily direct radiation at normal incidence at New Delhi has also been studied. It has been found that maximum global radiation is 30 MJ/m 2 /day for a south facing tilted surface, 21 MJ/m 2 /day for a south wall, 18 MJ/m 2 /day for an east west wall and 12 MJ/m 2 /day for a north wall. Maximum direct radiation at normal incidence at New Delhi is also 30 MJ/m 2 /day. For a south facing tilted surface, nearly 80% of the days have energy between 21-27 MJ/m 2 /day. Atmospheric transmittance for direct radiation is seen to vary from 20% in July to 52% in November
SEDA: A software package for the Statistical Earthquake Data Analysis
Lombardi, A. M.
2017-03-01
In this paper, the first version of the software SEDA (SEDAv1.0), designed to help seismologists statistically analyze earthquake data, is presented. The package consists of a user-friendly Matlab-based interface, which allows the user to easily interact with the application, and a computational core of Fortran codes, to guarantee the maximum speed. The primary factor driving the development of SEDA is to guarantee the research reproducibility, which is a growing movement among scientists and highly recommended by the most important scientific journals. SEDAv1.0 is mainly devoted to produce accurate and fast outputs. Less care has been taken for the graphic appeal, which will be improved in the future. The main part of SEDAv1.0 is devoted to the ETAS modeling. SEDAv1.0 contains a set of consistent tools on ETAS, allowing the estimation of parameters, the testing of model on data, the simulation of catalogs, the identification of sequences and forecasts calculation. The peculiarities of routines inside SEDAv1.0 are discussed in this paper. More specific details on the software are presented in the manual accompanying the program package.
Statistical analysis of the main diseases among atomic bomb survivors
International Nuclear Information System (INIS)
Hamada, Tadao; Kuramoto, Kiyoshi; Nambu, Shigeru
1988-01-01
Diseases found in 2,104 consequetive inpatients between April 1981 and March 1986 were statistically analyzed. The incidence of disease increased in the following order: diabetes mellitus > heart disease > cerebrovascular disorder > malignancy > hypertensive disease > arteriosclerosis > osteoarthritis. Malignancy is the most common cause of death or the highest mortality rate, followed by heart disease, cerebrovascular disorder, and liver cirrhosis. For the number of autopsy, the order of diseases was: malignancy, cardiovascular disease, gastrointestinal disease, respiratory tract disease, endocrine disease, and hematopoietic disease; for the incidence of autopsy, the order was: liver cirrhosis, diabetes mellitus, cerebrovascular disorder, malignancy, and heart disease. Malignancy accounted for 23 % of the inpatients. The incidence of malignancy increased in the following organs: stomach > liver > colon > lung > breast > biliary tract > esophagus. The incidence of leukemia was low. There was no definitive correlation between the incidence of malignancy and exposure distance, although the incidence of breast cancer tended to be high in the group exposed at ≤2,000 m from the hypocenter. According to age class, gastric cancer was frequent in patients less than 40 years and more than 60 years. Liver cancer was the most common in the sixtieth decade of life of men. The incidence of lung cancer increased with advancing age; the incidence of breast cancer was higher in younger patients. (Namekawa, K.)
Statistical analysis about corrosion in nuclear power plants
International Nuclear Information System (INIS)
Naquid G, C.; Medina F, A.; Zamora R, L.
1999-01-01
Nowadays, it has been carried out the investigations related with the structure degradation mechanisms, systems or and components in the nuclear power plants, since a lot of the involved processes are the responsible of the reliability of these ones, of the integrity of their components, of the safety aspects and others. This work presents the statistics of the studies related with materials corrosion in its wide variety and specific mechanisms. These exist at world level in the PWR, BWR, and WWER reactors, analysing the AIRS (Advanced Incident Reporting System) during the period between 1993-1998 in the two first plants in during the period between 1982-1995 for the WWER. The factors identification allows characterize them as those which apply, they are what have happen by the presence of some corrosion mechanism. Those which not apply, these are due to incidental by natural factors, mechanical failures and human errors. Finally, the total number of cases analysed, they correspond to the total cases which apply and not apply. (Author)
AutoBayes: A System for Generating Data Analysis Programs from Statistical Models
Fischer, Bernd; Schumann, Johann
2003-01-01
Data analysis is an important scientific task which is required whenever information needs to be extracted from raw data. Statistical approaches to data analysis, which use methods from probability theory and numerical analysis, are well-founded but dificult to implement: the development of a statistical data analysis program for any given application is time-consuming and requires substantial knowledge and experience in several areas. In this paper, we describe AutoBayes, a program synthesis...
Ensor, Joie; Burke, Danielle L; Snell, Kym I E; Hemming, Karla; Riley, Richard D
2018-05-18
Researchers and funders should consider the statistical power of planned Individual Participant Data (IPD) meta-analysis projects, as they are often time-consuming and costly. We propose simulation-based power calculations utilising a two-stage framework, and illustrate the approach for a planned IPD meta-analysis of randomised trials with continuous outcomes where the aim is to identify treatment-covariate interactions. The simulation approach has four steps: (i) specify an underlying (data generating) statistical model for trials in the IPD meta-analysis; (ii) use readily available information (e.g. from publications) and prior knowledge (e.g. number of studies promising IPD) to specify model parameter values (e.g. control group mean, intervention effect, treatment-covariate interaction); (iii) simulate an IPD meta-analysis dataset of a particular size from the model, and apply a two-stage IPD meta-analysis to obtain the summary estimate of interest (e.g. interaction effect) and its associated p-value; (iv) repeat the previous step (e.g. thousands of times), then estimate the power to detect a genuine effect by the proportion of summary estimates with a significant p-value. In a planned IPD meta-analysis of lifestyle interventions to reduce weight gain in pregnancy, 14 trials (1183 patients) promised their IPD to examine a treatment-BMI interaction (i.e. whether baseline BMI modifies intervention effect on weight gain). Using our simulation-based approach, a two-stage IPD meta-analysis has meta-analysis was appropriate. Pre-specified adjustment for prognostic factors would increase power further. Incorrect dichotomisation of BMI would reduce power by over 20%, similar to immediately throwing away IPD from ten trials. Simulation-based power calculations could inform the planning and funding of IPD projects, and should be used routinely.
Open Access Publishing Trend Analysis: Statistics beyond the Perception
Poltronieri, Elisabetta; Bravo, Elena; Curti, Moreno; Maurizio Ferri,; Mancini, Cristina
2016-01-01
Introduction: The purpose of this analysis was twofold: to track the number of open access journals acquiring impact factor, and to investigate the distribution of subject categories pertaining to these journals. As a case study, journals in which the researchers of the National Institute of Health (Istituto Superiore di Sanità) in Italy have…
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
Thermogravimetric analysis of multi-stage hydropyrolysis of different coals
Energy Technology Data Exchange (ETDEWEB)
Li, W.; Wang, N.; Li, B [Chinese Academy of Sciences, Taiyuan (China). State Key Lab. of Coal Conversion
2001-09-01
Based on the characteristic of hydropyrolysis (HyPy), a multi-stage MHyPy of different coals was investigated using thermogravimetry. The results show that keeping the near peak temperature for some time in HyPy process can obviously increase the conversion rate, which is believed due to the full match between formation rate of free radicals and supply of hydrogen. The fast heating in MHyPy process results in the same conversion rate as that of the slow heating in HyPy process, which leads to the less reaction time and high yield of oil. The effect of MHyPy depends on the coal structure itself and it is notable for the coal with high H/C ratio. This suggests that the external hydrogen promotes the reaction between intrinsic hydrogen and free radicals. The MHyPy improves the removal of sulfur and nitrogen. 5 refs., 7 figs., 2 tabs.
Statistical 21-cm Signal Separation via Gaussian Process Regression Analysis
Mertens, F. G.; Ghosh, A.; Koopmans, L. V. E.
2018-05-01
Detecting and characterizing the Epoch of Reionization and Cosmic Dawn via the redshifted 21-cm hyperfine line of neutral hydrogen will revolutionize the study of the formation of the first stars, galaxies, black holes and intergalactic gas in the infant Universe. The wealth of information encoded in this signal is, however, buried under foregrounds that are many orders of magnitude brighter. These must be removed accurately and precisely in order to reveal the feeble 21-cm signal. This requires not only the modeling of the Galactic and extra-galactic emission, but also of the often stochastic residuals due to imperfect calibration of the data caused by ionospheric and instrumental distortions. To stochastically model these effects, we introduce a new method based on `Gaussian Process Regression' (GPR) which is able to statistically separate the 21-cm signal from most of the foregrounds and other contaminants. Using simulated LOFAR-EoR data that include strong instrumental mode-mixing, we show that this method is capable of recovering the 21-cm signal power spectrum across the entire range k = 0.07 - 0.3 {h cMpc^{-1}}. The GPR method is most optimal, having minimal and controllable impact on the 21-cm signal, when the foregrounds are correlated on frequency scales ≳ 3 MHz and the rms of the signal has σ21cm ≳ 0.1 σnoise. This signal separation improves the 21-cm power-spectrum sensitivity by a factor ≳ 3 compared to foreground avoidance strategies and enables the sensitivity of current and future 21-cm instruments such as the Square Kilometre Array to be fully exploited.
Distribution-level electricity reliability: Temporal trends using statistical analysis
International Nuclear Information System (INIS)
Eto, Joseph H.; LaCommare, Kristina H.; Larsen, Peter; Todd, Annika; Fisher, Emily
2012-01-01
This paper helps to address the lack of comprehensive, national-scale information on the reliability of the U.S. electric power system by assessing trends in U.S. electricity reliability based on the information reported by the electric utilities on power interruptions experienced by their customers. The research analyzes up to 10 years of electricity reliability information collected from 155 U.S. electric utilities, which together account for roughly 50% of total U.S. electricity sales. We find that reported annual average duration and annual average frequency of power interruptions have been increasing over time at a rate of approximately 2% annually. We find that, independent of this trend, installation or upgrade of an automated outage management system is correlated with an increase in the reported annual average duration of power interruptions. We also find that reliance on IEEE Standard 1366-2003 is correlated with higher reported reliability compared to reported reliability not using the IEEE standard. However, we caution that we cannot attribute reliance on the IEEE standard as having caused or led to higher reported reliability because we could not separate the effect of reliance on the IEEE standard from other utility-specific factors that may be correlated with reliance on the IEEE standard. - Highlights: ► We assess trends in electricity reliability based on the information reported by the electric utilities. ► We use rigorous statistical techniques to account for utility-specific differences. ► We find modest declines in reliability analyzing interruption duration and frequency experienced by utility customers. ► Installation or upgrade of an OMS is correlated to an increase in reported duration of power interruptions. ► We find reliance in IEEE Standard 1366 is correlated with higher reported reliability.
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 analysis of joint toxicity in biological growth experiments
DEFF Research Database (Denmark)
Spliid, Henrik; Tørslev, J.
1994-01-01
The authors formulate a model for the analysis of designed biological growth experiments where a mixture of toxicants is applied to biological target organisms. The purpose of such experiments is to assess the toxicity of the mixture in comparison with the toxicity observed when the toxicants are...... is applied on data from an experiment where inhibition of the growth of the bacteria Pseudomonas fluorescens caused by different mixtures of pentachlorophenol and aniline was studied.......The authors formulate a model for the analysis of designed biological growth experiments where a mixture of toxicants is applied to biological target organisms. The purpose of such experiments is to assess the toxicity of the mixture in comparison with the toxicity observed when the toxicants...
Statistical Analysis for Test Papers with Software SPSS
Institute of Scientific and Technical Information of China (English)
张燕君
2012-01-01
Test paper evaluation is an important work for the management of tests, which results are significant bases for scientific summation of teaching and learning. Taking an English test paper of high students’monthly examination as the object, it focuses on the interpretation of SPSS output concerning item and whole quantitative analysis of papers. By analyzing and evaluating the papers, it can be a feedback for teachers to check the students’progress and adjust their teaching process.
Practical guidance for statistical analysis of operational event data
International Nuclear Information System (INIS)
Atwood, C.L.
1995-10-01
This report presents ways to avoid mistakes that are sometimes made in analysis of operational event data. It then gives guidance on what to do when a model is rejected, a list of standard types of models to consider, and principles for choosing one model over another. For estimating reliability, it gives advice on which failure modes to model, and moment formulas for combinations of failure modes. The issues are illustrated with many examples and case studies
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.
La Gamba, Fabiola; Corrao, Giovanni; Romio, Silvana; Sturkenboom, Miriam; Trifirò, Gianluca; Schink, Tania; de Ridder, Maria
2017-10-01
Clustering of patients in databases is usually ignored in one-stage meta-analysis of multi-database studies using matched case-control data. The aim of this study was to compare bias and efficiency of such a one-stage meta-analysis with a two-stage meta-analysis. First, we compared the approaches by generating matched case-control data under 5 simulated scenarios, built by varying: (1) the exposure-outcome association; (2) its variability among databases; (3) the confounding strength of one covariate on this association; (4) its variability; and (5) the (heterogeneous) confounding strength of two covariates. Second, we made the same comparison using empirical data from the ARITMO project, a multiple database study investigating the risk of ventricular arrhythmia following the use of medications with arrhythmogenic potential. In our study, we specifically investigated the effect of current use of promethazine. Bias increased for one-stage meta-analysis with increasing (1) between-database variance of exposure effect and (2) heterogeneous confounding generated by two covariates. The efficiency of one-stage meta-analysis was slightly lower than that of two-stage meta-analysis for the majority of investigated scenarios. Based on ARITMO data, there were no evident differences between one-stage (OR = 1.50, CI = [1.08; 2.08]) and two-stage (OR = 1.55, CI = [1.12; 2.16]) approaches. When the effect of interest is heterogeneous, a one-stage meta-analysis ignoring clustering gives biased estimates. Two-stage meta-analysis generates estimates at least as accurate and precise as one-stage meta-analysis. However, in a study using small databases and rare exposures and/or outcomes, a correct one-stage meta-analysis becomes essential. Copyright © 2017 John Wiley & Sons, Ltd.
Tanavalee, Chotetawan; Luksanapruksa, Panya; Singhatanadgige, Weerasak
2016-06-01
Microsoft Excel (MS Excel) is a commonly used program for data collection and statistical analysis in biomedical research. However, this program has many limitations, including fewer functions that can be used for analysis and a limited number of total cells compared with dedicated statistical programs. MS Excel cannot complete analyses with blank cells, and cells must be selected manually for analysis. In addition, it requires multiple steps of data transformation and formulas to plot survival analysis graphs, among others. The Megastat add-on program, which will be supported by MS Excel 2016 soon, would eliminate some limitations of using statistic formulas within MS Excel.
Wittenberg, P; Sever, K; Knoth, S; Sahin, N; Bondarenko, J
2013-01-01
Due to substantial progress made in road safety in the last ten years, the European Union (EU) renewed the ambitious agreement of halving the number of persons killed on the roads within the next decade. In this paper we develop a method that aims at finding an optimal target for each nation, in terms of being as achievable as possible, and with the cumulative EU target being reached. Targets as an important component in road safety policy are given as reduction rate or as absolute number of road traffic deaths. Determination of these quantitative road safety targets (QRST) is done by a top-down approach, formalized in a multi-stage adjustment procedure. Different QRST are derived under consideration of recent research. The paper presents a method to break the national target further down to regional targets in case of the German Federal States. Generalized linear models are fitted to data in the period 1991-2010. Our model selection procedure chooses various models for the EU and solely log-linear models for the German Federal States. If the proposed targets for the EU Member States are attained, the sum of fatalities should not exceed the total value of 15,465 per year by 2020. Both, the mean level and the range of mortality rates within the EU could be lowered from 28-113 in 2010 to 17-41 per million inhabitants in 2020. This study provides an alternative to the determination of safety targets by political commitments only, taking the history of road fatalities trends and population into consideration. Copyright © 2012 Elsevier Ltd. All rights reserved.
The art of data analysis how to answer almost any question using basic statistics
Jarman, Kristin H
2013-01-01
A friendly and accessible approach to applying statistics in the real worldWith an emphasis on critical thinking, The Art of Data Analysis: How to Answer Almost Any Question Using Basic Statistics presents fun and unique examples, guides readers through the entire data collection and analysis process, and introduces basic statistical concepts along the way.Leaving proofs and complicated mathematics behind, the author portrays the more engaging side of statistics and emphasizes its role as a problem-solving tool. In addition, light-hearted case studies
Statistical Power Analysis with Missing Data A Structural Equation Modeling Approach
Davey, Adam
2009-01-01
Statistical power analysis has revolutionized the ways in which we conduct and evaluate research. Similar developments in the statistical analysis of incomplete (missing) data are gaining more widespread applications. This volume brings statistical power and incomplete data together under a common framework, in a way that is readily accessible to those with only an introductory familiarity with structural equation modeling. It answers many practical questions such as: How missing data affects the statistical power in a study How much power is likely with different amounts and types
International Nuclear Information System (INIS)
Hirao, Keiichi; Yamane, Toshimi; Minamino, Yoritoshi
1991-01-01
This report is to show how the life due to stress corrosion cracking breakdown of fuel cladding tubes is evaluated by applying the statistical techniques to that examined by a few testing methods. The statistical distribution of the limiting values of constant load stress corrosion cracking life, the statistical analysis by making the probabilistic interpretation of constant load stress corrosion cracking life, and the statistical analysis of stress corrosion cracking life by the slow strain rate test (SSRT) method are described. (K.I.)
Some statistical design and analysis aspects for NAEG studies
International Nuclear Information System (INIS)
Gilbert, R.O.; Eberhardt, L.L.
1975-01-01
Some of the design and analysis aspects of the NAEG studies at safety-shot sites are reviewed in conjunction with discussions of possible new approaches. The use of double sampling to estimate inventories is suggested as a means of obtaining data for estimating the geographical distribution of plutonium using computer contouring programs. The lack of estimates of error for plutonium contours is noted and a regression approach discussed for obtaining such estimates. The kinds of new data that are now available for analysis from A site of Area 11 and the four Tonopah Test Range (TTR) sites are outlined, and the need for a closer look at methods for analyzing ratio-type data is pointed out. The necessity for thorough planning of environmental sampling programs is emphasized in order to obtain the maximum amount of information for fixed cost. Some general planning aspects of new studies at nuclear sites and experimental clean-up plots are discussed, as is the planning of interlaboratory comparisons. (U.S.)
Analysis of compressive fracture in rock using statistical techniques
Energy Technology Data Exchange (ETDEWEB)
Blair, S.C.
1994-12-01
Fracture of rock in compression is analyzed using a field-theory model, and the processes of crack coalescence and fracture formation and the effect of grain-scale heterogeneities on macroscopic behavior of rock are studied. The model is based on observations of fracture in laboratory compression tests, and incorporates assumptions developed using fracture mechanics analysis of rock fracture. The model represents grains as discrete sites, and uses superposition of continuum and crack-interaction stresses to create cracks at these sites. The sites are also used to introduce local heterogeneity. Clusters of cracked sites can be analyzed using percolation theory. Stress-strain curves for simulated uniaxial tests were analyzed by studying the location of cracked sites, and partitioning of strain energy for selected intervals. Results show that the model implicitly predicts both development of shear-type fracture surfaces and a strength-vs-size relation that are similar to those observed for real rocks. Results of a parameter-sensitivity analysis indicate that heterogeneity in the local stresses, attributed to the shape and loading of individual grains, has a first-order effect on strength, and that increasing local stress heterogeneity lowers compressive strength following an inverse power law. Peak strength decreased with increasing lattice size and decreasing mean site strength, and was independent of site-strength distribution. A model for rock fracture based on a nearest-neighbor algorithm for stress redistribution is also presented and used to simulate laboratory compression tests, with promising results.
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.
Statistical methods for the forensic analysis of striated tool marks
Energy Technology Data Exchange (ETDEWEB)
Hoeksema, Amy Beth [Iowa State Univ., Ames, IA (United States)
2013-01-01
In forensics, fingerprints can be used to uniquely identify suspects in a crime. Similarly, a tool mark left at a crime scene can be used to identify the tool that was used. However, the current practice of identifying matching tool marks involves visual inspection of marks by forensic experts which can be a very subjective process. As a result, declared matches are often successfully challenged in court, so law enforcement agencies are particularly interested in encouraging research in more objective approaches. Our analysis is based on comparisons of profilometry data, essentially depth contours of a tool mark surface taken along a linear path. In current practice, for stronger support of a match or non-match, multiple marks are made in the lab under the same conditions by the suspect tool. We propose the use of a likelihood ratio test to analyze the difference between a sample of comparisons of lab tool marks to a field tool mark, against a sample of comparisons of two lab tool marks. Chumbley et al. (2010) point out that the angle of incidence between the tool and the marked surface can have a substantial impact on the tool mark and on the effectiveness of both manual and algorithmic matching procedures. To better address this problem, we describe how the analysis can be enhanced to model the effect of tool angle and allow for angle estimation for a tool mark left at a crime scene. With sufficient development, such methods may lead to more defensible forensic analyses.
Product analysis of catalytic multi-stage hydropyrolysis of coal
Energy Technology Data Exchange (ETDEWEB)
Li, W.; Wang, N.; Li, B. [Chinese Academy of Sciences, Taiyuan (China). State Key Lab. of Coal Conversion
2002-05-01
Multi-stage hydropyrolysis (MHyPy) and hydropyrolysis (HyPy) of Xundian lignite, with MoS{sub 2} as the catalyst, were performed in a fixed bed reactor. The product distribution and property were investigated in detail. The results show that the tar yield increases to 63.9% during MHyPy compared with that of 51.8% in HyPy, while the gas yield decreases by 50%. The tar composition does not make big difference between MHyPy and HyPy. However, the light aromatics in the tar from MHyPy increase remarkably by 42%, 37.8% and 115.4% for BTX, PCX and naphthalene respectively. The specific surface area of char from MHyPy is larger than that from HyPy. The average pore diameter of char from MHyPy is smaller than that from HyPy, while the pore volume increases by 100% compared with that from HyPy. The catalytic MHyPy has an obvious advantage over HyPy. 10 refs., 8 figs., 3 tabs.