Jung, Sin-Ho
2015-05-01
Phase II trials have been very widely conducted and published every year for cancer clinical research. In spite of the fast progress in design and analysis methods, single-arm two-stage design is still the most popular for phase II cancer clinical trials. Because of their small sample sizes, statistical methods based on large sample approximation are not appropriate for design and analysis of phase II trials. As a prospective clinical research, the analysis method of a phase II trial is predetermined at the design stage and it is analyzed during and at the end of the trial as planned by the design. The analysis method of a trial should be matched with the design method. For two-stage single arm phase II trials, Simon's method has been the standards for choosing an optimal design, but the resulting data have been analyzed and published ignoring the two-stage design aspect with small sample sizes. In this article, we review analysis methods that exactly get along with the exact two-stage design method. We also discuss some statistical methods to improve the existing design and analysis methods for single-arm two-stage phase II trials. Copyright © 2015 Elsevier Inc. All rights reserved.
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
This RS code is to do Object-by-Object analysis of each Object's sub-objects, e.g. statistical analysis of an object's individual image data pixels. Statistics, such as percentiles (so-called "quartiles") are derived by the process, but the return of that can only be a Scene Variable, not an Object...... an analysis of the values of the object's pixels in MS-Excel. The shell of the proceedure could also be used for purposes other than just the derivation of Object - Sub-object statistics, e.g. rule-based assigment processes....... Variable. This procedure was developed in order to be able to export objects as ESRI shape data with the 90-percentile of the Hue of each object's pixels as an item in the shape attribute table. This procedure uses a sub-level single pixel chessboard segmentation, loops for each of the objects...
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.
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 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).
Statistical finite element analysis.
Khalaji, Iman; Rahemifar, Kaamran; Samani, Abbas
2008-01-01
A novel technique is introduced for tissue deformation and stress analysis. Compared to the conventional Finite Element method, this technique is orders of magnitude faster and yet still very accurate. The proposed technique uses preprocessed data obtained from FE analyses of a number of similar objects in a Statistical Shape Model framework as described below. This technique takes advantage of the fact that the body organs have limited variability, especially in terms of their geometry. As such, it is well suited for calculating tissue displacements of body organs. The proposed technique can be applied in many biomedical applications such as image guided surgery, or virtual reality environment development where tissue behavior is simulated for training purposes.
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
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.
Applied multivariate statistical analysis
National Research Council Canada - National Science Library
Johnson, Richard Arnold; Wichern, Dean W
1988-01-01
.... The authors hope that their discussions will meet the needs of experimental scientists, in a wide variety of subject matter areas, as a readable introduciton to the staistical analysis of multvariate observations...
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....
Pyrotechnic Shock Analysis Using Statistical Energy Analysis
2015-10-23
2013. 3. Lyon, Richard H., and DeJong, Richard G., “ Theory and Application of Statistical Energy Analysis, 2nd Edition,” Butterworth-Heinemann, 1995... Dalton , Eric C., “Ballistic Shock Response Prediction through the Synergistic Use of Statistical Energy Analysis, Finite Element Analysis, and
Statistical methods for bioimpedance analysis
Directory of Open Access Journals (Sweden)
Christian Tronstad
2014-04-01
Full Text Available This paper gives a basic overview of relevant statistical methods for the analysis of bioimpedance measurements, with an aim to answer questions such as: How do I begin with planning an experiment? How many measurements do I need to take? How do I deal with large amounts of frequency sweep data? Which statistical test should I use, and how do I validate my results? Beginning with the hypothesis and the research design, the methodological framework for making inferences based on measurements and statistical analysis is explained. This is followed by a brief discussion on correlated measurements and data reduction before an overview is given of statistical methods for comparison of groups, factor analysis, association, regression and prediction, explained in the context of bioimpedance research. The last chapter is dedicated to the validation of a new method by different measures of performance. A flowchart is presented for selection of statistical method, and a table is given for an overview of the most important terms of performance when evaluating new measurement technology.
Kalinowska, Barbara; Fabian, Piotr; Stąpor, Katarzyna; Roterman, Irena
2015-07-01
The polypeptide chain folding process appears to be a multi-stage phenomenon. The scientific community has recently devoted much attention to early stages of this process, with numerous attempts at simulating them—either experimentally or in silico. This paper presents a comparative analysis of the predicted and observed results of folding simulations. The proposed technique, based on statistical dictionaries, yields a global accuracy of 57 %—a marked improvement over older approaches (with an accuracy of approximately 46 %).
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
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 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...
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
Demanuele, Charmaine; Bähner, Florian; Plichta, Michael M; Kirsch, Peter; Tost, Heike; Meyer-Lindenberg, Andreas; Durstewitz, Daniel
2015-01-01
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 functional magnetic resonance imaging (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 (RAM) 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
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
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.
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 by Statistical Physics Model for the STOCK Markets
Wang, Tiansong; Wang, Jun; Fan, Bingli
A new stochastic stock price model of stock markets based on the contact process of the statistical physics systems is presented in this paper, where the contact model is a continuous time Markov process, one interpretation of this model is as a model for the spread of an infection. Through this model, the statistical properties of Shanghai Stock Exchange (SSE) and Shenzhen Stock Exchange (SZSE) are studied. In the present paper, the data of SSE Composite Index and the data of SZSE Component Index are analyzed, and the corresponding simulation is made by the computer computation. Further, we investigate the statistical properties, fat-tail phenomena, the power-law distributions, and the long memory of returns for these indices. The techniques of skewness-kurtosis test, Kolmogorov-Smirnov test, and R/S analysis are applied to study the fluctuation characters of the stock price returns.
Instant Replay: Investigating statistical Analysis in Sports
Sidhu, Gagan
2011-01-01
Technology has had an unquestionable impact on the way people watch sports. Along with this technological evolution has come a higher standard to ensure a good viewing experience for the casual sports fan. It can be argued that the pervasion of statistical analysis in sports serves to satiate the fan's desire for detailed sports statistics. The goal of statistical analysis in sports is a simple one: to eliminate subjective analysis. In this paper, we review previous work that attempts to anal...
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.
Morphological Analysis for Statistical Machine Translation
National Research Council Canada - National Science Library
Lee, Young-Suk
2004-01-01
We present a novel morphological analysis technique which induces a morphological and syntactic symmetry between two languages with highly asymmetrical morphological structures to improve statistical...
Match statistics related to winning in the group stage of 2014 Brazil FIFA World Cup.
Liu, Hongyou; Gomez, Miguel-Ángel; Lago-Peñas, Carlos; Sampaio, Jaime
2015-01-01
Identifying match statistics that strongly contribute to winning in football matches is a very important step towards a more predictive and prescriptive performance analysis. The current study aimed to determine relationships between 24 match statistics and the match outcome (win, loss and draw) in all games and close games of the group stage of FIFA World Cup (2014, Brazil) by employing the generalised linear model. The cumulative logistic regression was run in the model taking the value of each match statistic as independent variable to predict the logarithm of the odds of winning. Relationships were assessed as effects of a two-standard-deviation increase in the value of each variable on the change in the probability of a team winning a match. Non-clinical magnitude-based inferences were employed and were evaluated by using the smallest worthwhile change. Results showed that for all the games, nine match statistics had clearly positive effects on the probability of winning (Shot, Shot on Target, Shot from Counter Attack, Shot from Inside Area, Ball Possession, Short Pass, Average Pass Streak, Aerial Advantage and Tackle), four had clearly negative effects (Shot Blocked, Cross, Dribble and Red Card), other 12 statistics had either trivial or unclear effects. While for the close games, the effects of Aerial Advantage and Yellow Card turned to trivial and clearly negative, respectively. Information from the tactical modelling can provide a more thorough and objective match understanding to coaches and performance analysts for evaluating post-match performances and for scouting upcoming oppositions.
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)
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 ANALYSIS OF MONETARY POLICY INDICATORS VARIABILITY
Directory of Open Access Journals (Sweden)
ANAMARIA POPESCU
2016-10-01
Full Text Available This paper attempts to characterize through statistical indicators of statistical data that we have available. The purpose of this paper is to present statistical indicators, primary and secondary, simple and synthetic, which is frequently used for statistical characterization of statistical series. We can thus analyze central tendency, and data variability, form and concentration distributions package data using analytical tools in Microsoft Excel that enables automatic calculation of descriptive statistics using Data Analysis option from the Tools menu. We will also study the links which exist between statistical variables can be studied using two techniques, correlation and regression. From the analysis of monetary policy in the period 2003 - 2014 and information provided by the website of the National Bank of Romania (BNR seems to be a certain tendency towards eccentricity and asymmetry of financial data series.
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
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 ...
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...
Statistical distribution analysis of rubber fatigue data
DeRudder, J. L.
1981-10-01
Average rubber fatigue resistance has previously been related to such factors as elastomer type, cure system, cure temperature, and stress history. This paper extends this treatment to a full statistical analysis of rubber fatigue data. Analyses of laboratory fatigue data are used to predict service life. Particular emphasis is given to the prediction of early tire splice failures, and to adaptations of statistical fatigue analysis for the particular service conditions of the rubber industry.
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...
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.
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...
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.)
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
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).
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....... The statistical fits have generally been made using all data and the lower tail of the data. The Maximum Likelihood Method and the Least Square Technique have been used to estimate the statistical parameters in the selected distributions. The results show that the 2-parameter Weibull distribution gives the best...... 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...
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...
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;
Vapor Pressure Data Analysis and Statistics
2016-12-01
SUBJECT TERMS Vapor pressure Antoine equation Statistical analysis Clausius–Clapeyron equation Standard deviation Volatility Enthalpy of volatilization...11 5. Antoine Constants (Equation 3), Standard Deviations , and S for 1-Tetradecanol .............12 6. Vapor...13 7. Antoine Constants (Equation 3), Standard Deviations , and S for DEM ............................13 8. Vapor Pressures
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
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.
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
Statistical analysis of next generation sequencing data
Nettleton, Dan
2014-01-01
Next Generation Sequencing (NGS) is the latest high throughput technology to revolutionize genomic research. NGS generates massive genomic datasets that play a key role in the big data phenomenon that surrounds us today. To extract signals from high-dimensional NGS data and make valid statistical inferences and predictions, novel data analytic and statistical techniques are needed. This book contains 20 chapters written by prominent statisticians working with NGS data. The topics range from basic preprocessing and analysis with NGS data to more complex genomic applications such as copy number variation and isoform expression detection. Research statisticians who want to learn about this growing and exciting area will find this book useful. In addition, many chapters from this book could be included in graduate-level classes in statistical bioinformatics for training future biostatisticians who will be expected to deal with genomic data in basic biomedical research, genomic clinical trials and personalized med...
Robust statistics and geochemical data analysis
International Nuclear Information System (INIS)
Di, Z.
1987-01-01
Advantages of robust procedures over ordinary least-squares procedures in geochemical data analysis is demonstrated using NURE data from the Hot Springs Quadrangle, South Dakota, USA. Robust principal components analysis with 5% multivariate trimming successfully guarded the analysis against perturbations by outliers and increased the number of interpretable factors. Regression with SINE estimates significantly increased the goodness-of-fit of the regression and improved the correspondence of delineated anomalies with known uranium prospects. Because of the ubiquitous existence of outliers in geochemical data, robust statistical procedures are suggested as routine procedures to replace ordinary least-squares procedures
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.
Multivariate analysis: A statistical approach for computations
Michu, Sachin; Kaushik, Vandana
2014-10-01
Multivariate analysis is a type of multivariate statistical approach commonly used in, automotive diagnosis, education evaluating clusters in finance etc and more recently in the health-related professions. The objective of the paper is to provide a detailed exploratory discussion about factor analysis (FA) in image retrieval method and correlation analysis (CA) of network traffic. Image retrieval methods aim to retrieve relevant images from a collected database, based on their content. The problem is made more difficult due to the high dimension of the variable space in which the images are represented. Multivariate correlation analysis proposes an anomaly detection and analysis method based on the correlation coefficient matrix. Anomaly behaviors in the network include the various attacks on the network like DDOs attacks and network scanning.
Statistical Methods for Conditional Survival Analysis.
Jung, Sin-Ho; Lee, Ho Yun; Chow, Shein-Chung
2017-11-29
We investigate the survival distribution of the patients who have survived over a certain time period. This is called a conditional survival distribution. In this paper, we show that one-sample estimation, two-sample comparison and regression analysis of conditional survival distributions can be conducted using the regular methods for unconditional survival distributions that are provided by the standard statistical software, such as SAS and SPSS. We conduct extensive simulations to evaluate the finite sample property of these conditional survival analysis methods. We illustrate these methods with real clinical data.
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.
The CALORIES trial: statistical analysis plan.
Harvey, Sheila E; Parrott, Francesca; Harrison, David A; Mythen, Michael; Rowan, Kathryn M
2014-12-01
The CALORIES trial is a pragmatic, open, multicentre, randomised controlled trial (RCT) of the clinical effectiveness and cost-effectiveness of early nutritional support via the parenteral route compared with early nutritional support via the enteral route in unplanned admissions to adult general critical care units (CCUs) in the United Kingdom. The trial derives from the need for a large, pragmatic RCT to determine the optimal route of delivery for early nutritional support in the critically ill. To describe the proposed statistical analyses for the evaluation of the clinical effectiveness in the CALORIES trial. With the primary and secondary outcomes defined precisely and the approach to safety monitoring and data collection summarised, the planned statistical analyses, including prespecified subgroups and secondary analyses, were developed and are described. The primary outcome is all-cause mortality at 30 days. The primary analysis will be reported as a relative risk and absolute risk reduction and tested with the Fisher exact test. Prespecified subgroup analyses will be based on age, degree of malnutrition, acute severity of illness, mechanical ventilation at admission to the CCU, presence of cancer and time from CCU admission to commencement of early nutritional support. Secondary analyses include adjustment for baseline covariates. In keeping with best trial practice, we have developed, described and published a statistical analysis plan for the CALORIES trial and are placing it in the public domain before inspecting data from the trial.
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
Terminal-stage prognostic analysis in candidemia.
Takuma, Takahiro; Shoji, Hisashi; Niki, Yoshihito
2015-05-01
Candidemia has an extremely high mortality rate but is not always the direct cause of death. Therefore, determining the effect of candidemia on death is extremely difficult. We investigated prognostic factors in patients with culture-proven candidemia at 2 Japanese university teaching hospitals from April 2009 through May 2013. To examine the effects of comorbid conditions, the Charlson comorbidity index was determined, and patients were subjectively classified into 3 clinical prognostic stages (terminal [death expected within 1 month], semiterminal [death expected within 6 months], and nonterminal [expected to live more than 6 months]). The Cox proportional hazard model was used for univariate and multivariate analyses of factors possibly affecting survival. On univariate analysis, factors identified as associated with an increased mortality rate were: admission to an internal medicine department, Candida glabrata, immunosuppression, hypotension, hypoxemia, and a terminal prognostic stage. Factors associated with a decreased mortality rate were: serum albumin, endophthalmitis investigation, and nonterminal prognostic stage. The mortality rate was significantly related to the prognostic stage on multivariate analysis (P candidemia. More important than candidemia in causing the deaths of patients with candidemia were the patients' background and comorbidity status. Therefore, rigorous methods should be used when investigating causes of death in terminally ill patients with candidemia. Copyright © 2015 Japanese Society of Chemotherapy and The Japanese Association for Infectious Diseases. Published by Elsevier Ltd. All rights reserved.
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
STATISTICS, Program System for Statistical Analysis of Experimental Data
International Nuclear Information System (INIS)
Helmreich, F.
1991-01-01
1 - Description of problem or function: The package is composed of 83 routines, the most important of which are the following: BINDTR: Binomial distribution; HYPDTR: Hypergeometric distribution; POIDTR: Poisson distribution; GAMDTR: Gamma distribution; BETADTR: Beta-1 and Beta-2 distributions; NORDTR: Normal distribution; CHIDTR: Chi-square distribution; STUDTR : Distribution of 'Student's T'; FISDTR: Distribution of F; EXPDTR: Exponential distribution; WEIDTR: Weibull distribution; FRAKTIL: Calculation of the fractiles of the normal, chi-square, Student's, and F distributions; VARVGL: Test for equality of variance for several sample observations; ANPAST: Kolmogorov-Smirnov test and chi-square test of goodness of fit; MULIRE: Multiple linear regression analysis for a dependent variable and a set of independent variables; STPRG: Performs a stepwise multiple linear regression analysis for a dependent variable and a set of independent variables. At each step, the variable entered into the regression equation is the one which has the greatest amount of variance between it and the dependent variable. Any independent variable can be forced into or deleted from the regression equation, irrespective of its contribution to the equation. LTEST: Tests the hypotheses of linearity of the data. SPRANK: Calculates the Spearman rank correlation coefficient. 2 - Method of solution: VARVGL: The Bartlett's Test, the Cochran's Test and the Hartley's Test are performed in the program. MULIRE: The Gauss-Jordan method is used in the solution of the normal equations. STPRG: The abbreviated Doolittle method is used to (1) determine variables to enter into the regression, and (2) complete regression coefficient calculation. 3 - Restrictions on the complexity of the problem: VARVGL: The Hartley's Test is only performed if the sample observations are all of the same size
Statistical analysis of 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.
STATISTICAL ANALYSIS OF PUBLIC ADMINISTRATION PAY
Directory of Open Access Journals (Sweden)
Elena I. Dobrolyubova
2014-01-01
Full Text Available This article reviews the progress achieved inimproving the pay system in public administration and outlines the key issues to be resolved.The cross-country comparisons presented inthe article suggest high differentiation in pay levels depending on position held. In fact,this differentiation in Russia exceeds one in OECD almost twofold The analysis of theinternal pay structure demonstrates that thelow share of the base pay leads to perversenature of ‘stimulation elements’ of the paysystem which in fact appear to be used mostlyfor compensation purposes. The analysis of regional statistical data demonstrates thatdespite high differentiation among regionsin terms of their revenue potential, averagepublic ofﬁcial pay is strongly correlated withthe average regional pay.
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 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.
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
SMACS, Probabilistic Seismic Analysis Chain with Statistics
International Nuclear Information System (INIS)
Johnson, J.J.; Maslenikov, O.R.; Tiong, L.W.; Mraz, M.J.; Bumpus, S.; Gerhard, M.A.
1989-01-01
1 - Description of program or function: The SMACS (Seismic Methodology Analysis Chain with Statistics) system of computer programs is one of the major computational tools of the U.S. NRC Seismic Safety Margins Research Program (SSMRP). SMACS is comprised of the core program SMAX, which performs the SSI response analyses, five pre- processing programs, and two post-processors. The pre-processing programs include: GLAY and CLAN, which generate the nominal impedance matrices and wave scattering vectors for surface-founded structures; INSSIN, which projects the dynamic properties of structures to the foundation in the form of modal participation factors and mass matrices; SAPPAC, which projects the dynamic and pseudo-static properties of multiply-supported piping systems to the support locations, and LNGEN, which can be used to generate the multiplication factors to be applied to the nominal soil, structural, and subsystem properties for each of the response calculations in accounting for random variations of these properties. The post-processors are: PRESTO, which performs statistical operations on the raw data from the response vectors that SMAX produces to calculate best fit lognormal distributions for each response location, and CHANGO, which manipulates the data produced by PRESTO to produce other results of interest to the user. Also included is the computer program SAP4 (a modified version of the University of California, Berkeley SAPIV program), a general linear structural analysis program used for eigenvalue extractions and pseudo-static mode calculations of the models of major structures and subsystems. SAP4 is used to prepare input to the INSSIN and SAPPAC preprocessing programs. The GLAY and CLAN programs were originally developed by J.E. Luco (UCSD) and H.L. Wong (USC). 2 - Method of solution: SMACS performs repeated deterministic analyses, each analysis simulating an earthquake occurrence. Uncertainty is accounted for by performing many such analyses
R: a statistical environment for hydrological analysis
Zambrano-Bigiarini, Mauricio; Bellin, Alberto
2010-05-01
The free software environment for statistical computing and graphics "R" has been developed and it is maintained by statistical programmers, with the support of an increasing community of users with many different backgrounds, which allows access to both well-established and experimental techniques. Hydrological modelling practitioners spent large amount of time in pre- and post-processing data and results with traditional instruments. In this work "R" and some of its packages are presented as powerful tools to explore and extract patterns from raw information, to pre-process input data of hydrological models, and post-processing its results. In particular, examples are taken from analysing 30-years of daily data for a basin of 85000 km2, saving a large amount of time that could be better spent in doing analysis. In doing so, vectorial and raster GIS files were imported, for carrying out spatial and geostatistical analysis. Thousands of raw text files with time series of precipitation, temperature and streamflow were summarized and organized. Gauging stations to be used in the modelling process are selected according to the amount of days with information, and missing time series data are filled in using spatial interpolation. Time series on the gauging stations are summarized through daily, monthly and annual plots. Input files in dbase format are automatically created in a batch process. Results of a hydrological model are compared with observed values through plots and numerical goodness of fit indexes. Two packages specifically developed to assists hydrologists in the previous tasks are briefly presented. At the end, we think the "R" environment would be a valuable tool to support undergraduate and graduate education in hydrology, because it is helpful to capture the main features of large amount of data; it is a flexible and fully functional programming language, able to be interfaced to existing Fortran and C code and well suited to the ever growing demands
An R package for statistical provenance analysis
Vermeesch, Pieter; Resentini, Alberto; Garzanti, Eduardo
2016-05-01
This paper introduces provenance, a software package within the statistical programming environment R, which aims to facilitate the visualisation and interpretation of large amounts of sedimentary provenance data, including mineralogical, petrographic, chemical and isotopic provenance proxies, or any combination of these. provenance comprises functions to: (a) calculate the sample size required to achieve a given detection limit; (b) plot distributional data such as detrital zircon U-Pb age spectra as Cumulative Age Distributions (CADs) or adaptive Kernel Density Estimates (KDEs); (c) plot compositional data as pie charts or ternary diagrams; (d) correct the effects of hydraulic sorting on sandstone petrography and heavy mineral composition; (e) assess the settling equivalence of detrital minerals and grain-size dependence of sediment composition; (f) quantify the dissimilarity between distributional data using the Kolmogorov-Smirnov and Sircombe-Hazelton distances, or between compositional data using the Aitchison and Bray-Curtis distances; (e) interpret multi-sample datasets by means of (classical and nonmetric) Multidimensional Scaling (MDS) and Principal Component Analysis (PCA); and (f) simplify the interpretation of multi-method datasets by means of Generalised Procrustes Analysis (GPA) and 3-way MDS. All these tools can be accessed through an intuitive query-based user interface, which does not require knowledge of the R programming language. provenance is free software released under the GPL-2 licence and will be further expanded based on user feedback.
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.
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
Statistical modeling of CTV motion and deformation for IMRT of early-stage rectal cancer.
Bondar, Luiza; Intven, Martijn; Burbach, J P Maarten; Budiarto, Eka; Kleijnen, Jean-Paul; Philippens, Marielle; van Asselen, Bram; Seravalli, Enrica; Reerink, Onne; Raaymakers, Bas
2014-11-01
To derive and validate a statistical model of motion and deformation for the clinical target volume (CTV) of early-stage rectal cancer patients. For 16 patients, 4 to 5 magnetic resonance images (MRI) were acquired before each fraction was administered. The CTV was delineated on each MRI. Using a leave-one-out methodology, we constructed a population-based principal component analysis (PCA) model of the CTV motion and deformation of 15 patients, and we tested the model on the left-out patient. The modeling error was calculated as the amount of the CTV motion-deformation of the left-out-patient that could not be explained by the PCA model. Next, the PCA model was used to construct a PCA target volume (PCA-TV) by accumulating motion-deformations simulated by the model. A PCA planning target volume (PTV) was generated by expanding the PCA-TV by uniform margins. The PCA-PTV was compared with uniform and nonuniform CTV-to-PTV margins. To allow comparison, geometric margins were determined to ensure adequate coverage, and the volume difference between the PTV and the daily CTV (CTV-to-PTV volume) was calculated. The modeling error ranged from 0.9 ± 0.5 to 2.9 ± 2.1 mm, corresponding to a reduction of the CTV motion-deformation between 6% and 60% (average, 23% ± 11%). The reduction correlated with the magnitude of the CTV motion-deformation (P<.001, R=0.66). The PCA-TV and the CTV required 2-mm and 7-mm uniform margins, respectively. The nonuniform CTV-to-PTV margins were 4 mm in the left, right, inferior, superior, and posterior directions and 8 mm in the anterior direction. Compared to uniform and nonuniform CTV-to-PTV margins, the PCA-based PTV significantly decreased (P<.001) the average CTV-to-PTV volume by 128 ± 20 mL (49% ± 4%) and by 35 ± 6 mL (20% ± 3.5%), respectively. The CTV motion-deformation of a new patient can be explained by a population-based PCA model. A PCA model-generated PTV significantly improved sparing of organs at risk compared to uniform
First statistical analysis of Geant4 quality software metrics
Ronchieri, Elisabetta; Grazia Pia, Maria; Giacomini, Francesco
2015-12-01
Geant4 is a simulation system of particle transport through matter, widely used in several experimental areas from high energy physics and nuclear experiments to medical studies. Some of its applications may involve critical use cases; therefore they would benefit from an objective assessment of the software quality of Geant4. In this paper, we provide a first statistical evaluation of software metrics data related to a set of Geant4 physics packages. The analysis aims at identifying risks for Geant4 maintainability, which would benefit from being addressed at an early stage. The findings of this pilot study set the grounds for further extensions of the analysis to the whole of Geant4 and to other high energy physics software systems.
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...
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 Analysis of Bus Networks in India.
Chatterjee, Atanu; Manohar, Manju; Ramadurai, Gitakrishnan
2016-01-01
In this paper, we model the bus networks of six major Indian cities as graphs in L-space, and evaluate their various statistical properties. While airline and railway networks have been extensively studied, a comprehensive study on the structure and growth of bus networks is lacking. In India, where bus transport plays an important role in day-to-day commutation, it is of significant interest to analyze its topological structure and answer basic questions on its evolution, growth, robustness and resiliency. Although the common feature of small-world property is observed, our analysis reveals a wide spectrum of network topologies arising due to significant variation in the degree-distribution patterns in the networks. We also observe that these networks although, robust and resilient to random attacks are particularly degree-sensitive. Unlike real-world networks, such as Internet, WWW and airline, that are virtual, bus networks are physically constrained. Our findings therefore, throw light on the evolution of such geographically and constrained networks that will help us in designing more efficient bus networks in the future.
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.
Developments in statistical analysis in quantitative genetics
DEFF Research Database (Denmark)
Sorensen, Daniel
2009-01-01
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 ...
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...... has much to offer in analyzing the policy process....
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.
Statistical Analysis of Data for Timber Strengths
DEFF Research Database (Denmark)
Sørensen, John Dalsgaard; Hoffmeyer, P.
. The statistical fits have generally been made using all data (100%) and the lower tail (30%) of the data. The Maximum Likelihood Method and the Least Square Technique have been used to estimate the statistical parameters in the selected distributions. 8 different databases are analysed. The results show that 2......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......-parameter Weibull (and Normal) distributions give the best fits to the data available, especially if tail fits are used whereas the LogNormal distribution generally gives poor fit and larger coefficients of variation, especially if tail fits are used....
Analysis of Preference Data Using Intermediate Test Statistic Abstract
African Journals Online (AJOL)
PROF. O. E. OSUAGWU
2013-06-01
Jun 1, 2013 ... [5] Hill, I.D., Some Aspects of Election-to-fill one seat or many, Journal of Royal. Statistical Society A, No. 151, pp. 310-314. [6] Myers, R.H., A First Course in the Theorey of Linear Statistical Models, PWS-. KENT, Boston, 1991. [7] Taplin, R.H., The Statistical Analysis of Preference Data, Applied Statistics, No.
Tang, Z. Q.; Jiang, N.
2012-08-01
The hairpin packet's structure and its statistical scale in the later stage of bypass transition induced by a cylinder wake are investigated by time-resolved particle image velocimetry from the side and top view, respectively. Linear stochastic estimation is used to achieve the conditionally averaged velocity fields. For the side view case, the conditionally averaged structure consists of a series of swirling motions located along a line inclining at a large angle (18°) from the wall and a low-speed region occupied by the cylinder wake appearing right above them. In the ( x, z)-plane at the wall-normal height y/δ = 0.2, the dominant structures are shown to be the large-scale regions of low momentum elongated almost over 3δ along the streamwise. The low-speed regions are consistently bordered by small-scale counter-rotating vortice pairs organized in the streamwise with a statistical spanwise width of 0.55δ. The results suggest that in the later part of the transitional zone, the upward induction of the cylinder wake enhances both the wall-normal and spanwise extent of the hairpin packets.
Computer-Assisted Statistical Analysis: Mainframe or Microcomputer.
Shannon, David M.
1993-01-01
Describes a study that was designed to examine whether the computer attitudes of graduate students in a beginning statistics course differed based on their prior computer experience and the type of statistical analysis package used. Versions of statistical analysis packages using a mainframe and a microcomputer are compared. (14 references) (LRW)
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.
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.
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...
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 on andrological patients. I. Frequencies].
Nebe, K H; Schirren, C
1980-01-01
According a collective of 1619 andrological patients of the year 1975 some statistical data were given: age distribution, frequencies, frequency of sexual intercourse, anticonception and relation to age, coitus frequency and relation to age, impotence and relation to age, previous andrological treatment.
Commentary Discrepancy between statistical analysis method and ...
African Journals Online (AJOL)
Malawi University of Science and Technology, Thyolo, Malawi. 2. Department of Statistical Sciences, University of Cape Town, Cape Town, South Africa. 3. Malawi College of Medicine–Johns Hopkins University Research Project, College of Medicine, University of Malawi, Blantyre, Malawi. 4. Mahidol–Oxford Research Unit ...
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)
Statistical Analysis Of Reconnaissance Geochemical Data From ...
African Journals Online (AJOL)
, Co, Mo, Hg, Sb, Tl, Sc, Cr, Ni, La, W, V, U, Th, Bi, Sr and Ga in 56 stream sediment samples collected from Orle drainage system were subjected to univariate and multivariate statistical analyses. The univariate methods used include ...
Statistical 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 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
Individual participant data meta-analysis for a binary outcome: one-stage or two-stage?
Directory of Open Access Journals (Sweden)
Thomas P A Debray
Full Text Available BACKGROUND: A fundamental aspect of epidemiological studies concerns the estimation of factor-outcome associations to identify risk factors, prognostic factors and potential causal factors. Because reliable estimates for these associations are important, there is a growing interest in methods for combining the results from multiple studies in individual participant data meta-analyses (IPD-MA. When there is substantial heterogeneity across studies, various random-effects meta-analysis models are possible that employ a one-stage or two-stage method. These are generally thought to produce similar results, but empirical comparisons are few. OBJECTIVE: We describe and compare several one- and two-stage random-effects IPD-MA methods for estimating factor-outcome associations from multiple risk-factor or predictor finding studies with a binary outcome. One-stage methods use the IPD of each study and meta-analyse using the exact binomial distribution, whereas two-stage methods reduce evidence to the aggregated level (e.g. odds ratios and then meta-analyse assuming approximate normality. We compare the methods in an empirical dataset for unadjusted and adjusted risk-factor estimates. RESULTS: Though often similar, on occasion the one-stage and two-stage methods provide different parameter estimates and different conclusions. For example, the effect of erythema and its statistical significance was different for a one-stage (OR = 1.35, [Formula: see text] and univariate two-stage (OR = 1.55, [Formula: see text]. Estimation issues can also arise: two-stage models suffer unstable estimates when zero cell counts occur and one-stage models do not always converge. CONCLUSION: When planning an IPD-MA, the choice and implementation (e.g. univariate or multivariate of a one-stage or two-stage method should be prespecified in the protocol as occasionally they lead to different conclusions about which factors are associated with outcome. Though both
Methods of statistical analysis of fluctuating asymmetry
Directory of Open Access Journals (Sweden)
Zorina Anastasia
2012-10-01
Full Text Available Methodical problems concerning the practical use of fluctuating asymmetry level of bio-objects are considered. The questions connected with the variety of value asymmetry calculation methods and the use of asymmetry indicators efficiency and integrated indexes are discussed in detail. Discrepancy of research results when using several estimates of asymmetry is connected with their statistical properties and peculiarity of their normal variability which define sensitivity and operability of indicators. Concrete examples illustrating the negative influence of arithmetic transformations on the revealing properties of indicators are given: disturbance of normal distribution and the need of using rough nonparametric criteria , the increase of the importance of rare casual deviations, the introduction of additional variability components into an asymmetry level. Problems which arise in calculating asymmetry integrated indexes when signs unite with different levels of statistical parameters are separately considered. It is recommended to use the indicator of fluctuating asymmetry based on normalized deviation.
Statistical uncertainty analysis in reactor risk estimation
International Nuclear Information System (INIS)
Modarres, M.; Cadman, T.
1985-01-01
Two promising methods of statistical uncertainty evaluation for use in probabilistic risk assessment (PRA) are described, tested, and compared in this study. These two methods are the Bootsrap technique and the System Reduction technique. Both of these methods use binomial distributions to model all probability estimates. Necessary modifications to these two methods are discussed. These modifications are necessary for an objective use of the methods in the PRA's. The methods are applied to important generic pressurized water reactor transient and loss of coolant accident event trees. The results of this application are presented and compared. Finally, conclusions are drawn regarding the applicability of the methods and the results obtained in the study. It is concluded that both of the methods yield results which are comparable and that both can be used in statistical uncertainty evaluations under certain specified conditions. (orig.)
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...
Network analysis based on large deviation statistics
Miyazaki, Syuji
2007-07-01
A chaotic piecewise linear map whose statistical properties are identical to those of a random walk on directed graphs such as the world wide web (WWW) is constructed, and the dynamic quantity is analyzed in the framework of large deviation statistics. Gibbs measures include the weight factor appearing in the weighted average of the dynamic quantity, which can also quantitatively measure the importance of web sites. Currently used levels of importance in the commercial search engines are independent of search terms, which correspond to the stationary visiting frequency of each node obtained from a random walk on the network or equivalent chaotic dynamics. Levels of importance based on the Gibbs measure depend on each search term which is specified by the searcher. The topological conjugate transformation between one dynamical system with a Gibbs measure and another dynamical system whose standard invariant probability measure is identical to the Gibbs measure is also discussed.
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.
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
Multinomial analysis of behavior: statistical methods.
Koster, Jeremy; McElreath, Richard
2017-01-01
Behavioral ecologists frequently use observational methods, such as instantaneous scan sampling, to record the behavior of animals at discrete moments in time. We develop and apply multilevel, multinomial logistic regression models for analyzing such data. These statistical methods correspond to the multinomial character of the response variable while also accounting for the repeated observations of individuals that characterize behavioral datasets. Correlated random effects potentially reveal individual-level trade-offs across behaviors, allowing for models that reveal the extent to which individuals who regularly engage in one behavior also exhibit relatively more or less of another behavior. Using an example dataset, we demonstrate the estimation of these models using Hamiltonian Monte Carlo algorithms, as implemented in the RStan package in the R statistical environment. The supplemental files include a coding script and data that demonstrate auxiliary functions to prepare the data, estimate the models, summarize the posterior samples, and generate figures that display model predictions. We discuss possible extensions to our approach, including models with random slopes to allow individual-level behavioral strategies to vary over time and the need for models that account for temporal autocorrelation. These models can potentially be applied to a broad class of statistical analyses by behavioral ecologists, focusing on other polytomous response variables, such as behavior, habitat choice, or emotional states.
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 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 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.
Why Flash Type Matters: A Statistical Analysis
Mecikalski, Retha M.; Bitzer, Phillip M.; Carey, Lawrence D.
2017-09-01
While the majority of research only differentiates between intracloud (IC) and cloud-to-ground (CG) flashes, there exists a third flash type, known as hybrid flashes. These flashes have extensive IC components as well as return strokes to ground but are misclassified as CG flashes in current flash type analyses due to the presence of a return stroke. In an effort to show that IC, CG, and hybrid flashes should be separately classified, the two-sample Kolmogorov-Smirnov (KS) test was applied to the flash sizes, flash initiation, and flash propagation altitudes for each of the three flash types. The KS test statistically showed that IC, CG, and hybrid flashes do not have the same parent distributions and thus should be separately classified. Separate classification of hybrid flashes will lead to improved lightning-related research, because unambiguously classified hybrid flashes occur on the same order of magnitude as CG flashes for multicellular storms.
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 Martian surface
Landais, F.; Schmidt, F.; Lovejoy, S.
2015-10-01
We investigate the scaling properties of the topography of Mars [10]. Planetary topographic fields are well known to exhibit (mono)fractal behavior. Indeed, fractal formalism is efficient to reproduce the variability observed in topography. Still, a single fractal dimension is not enough to explain the huge variability and intermittency. Previous study have shown that fractal dimensions might be different from a region to another, excluding a general description at the planetary scale. In this project, we are analyzing the Martian topographic data with a multifractal formalism to study the scaling intermittency. In the multifractal paradigm, the local variation of the fractal dimension is interpreted as a statistical property of multifractal fields. The results suggest a multifractal behaviour from planetary scale down to 10 km. From 10 km to 600 m, the topography seems to be simple monofractal. This transition indicates a significant in the geological processes governing the Red Planet's surface.
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 analysis of earthquake ground motion parameters
Energy Technology Data Exchange (ETDEWEB)
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 analysis of concrete creep effects
International Nuclear Information System (INIS)
Floris, C.
1989-01-01
The principal sources of uncertainty in concrete creep effects are the following: uncertainty in the stochastic evolution in time of the mechanism of creep (internal uncertainty); uncertainty in the prediction of the properties of the materials; uncertainty in the stochastic evolution of environmental conditions; uncertainty of the theoretical models; errors of measurement. Interest in the random nature of concrete creep (and shrinkage) effects is discussed. The late beginning of the studies on this subject is perhaps due to their theoretical and computational complexity: nevertheless, since creep and shrinkage affect features of concrete structures as the residual prestressing force in prestressed sections, the stress redistribution in steel-concrete composite beams, deflections and deformations, stress distributions in non-homogenous structures, reactions due to delayed restraints and creep buckling, these studies are very important. This paper is aimed to find the statistics of some of these effects taking into the account the third type of source of uncertainty
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 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 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 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/
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)
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
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…
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.
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
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...... smoothing (e.g., as in complex smoothing) with respect to the original RTF statistics. More specifically, the RTF statistics, derived after the complex smoothing calculation, are compared to the original statistics across space inside typical rooms, by varying the source, the receiver position...... 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 Image Analysis of Longitudinal RAVENS Images
Directory of Open Access Journals (Sweden)
Seonjoo eLee
2015-10-01
Full Text Available Regional analysis of volumes examined in normalized space (RAVENS are transformation images used in the study of brain morphometry. In this paper, RAVENS images are analyzed using a longitudinal variant of voxel-based morphometry (VBM and longitudinal functional principal component analysis (LFPCA for high-dimensional images. We demonstrate that the latter overcomes the limitations of standard longitudinal VBM analyses, which does not separate registration errors from other longitudinal changes and baseline patterns. This is especially important in contexts where longitudinal changes are only a small fraction of the overall observed variability, which is typical in normal aging and many chronic diseases. Our simulation study shows that LFPCA effectively separates registration error from baseline and longitudinal signals of interest by decomposing RAVENS images measured at multiple visits into three components: a subject-specific imaging random intercept that quantifies the cross-sectional variability, a subject-specific imaging slope that quantifies the irreversible changes over multiple visits, and a subject-visit specific imaging deviation. We describe strategies to identify baseline/longitudinal variation and registration errors combined with covariates of interest. Our analysis suggests that specific regional brain atrophy and ventricular enlargement are associated with multiple sclerosis (MS disease progression.
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)
Domain analysis and modeling to improve comparability of health statistics.
Okada, M; Hashimoto, H; Ohida, T
2001-01-01
Health statistics is an essential element to improve the ability of managers of health institutions, healthcare researchers, policy makers, and health professionals to formulate appropriate course of reactions and to make decisions based on evidence. To ensure adequate health statistics, standards are of critical importance. A study on healthcare statistics domain analysis is underway in an effort to improve usability and comparability of health statistics. The ongoing study focuses on structuring the domain knowledge and making the knowledge explicit with a data element dictionary being the core. Supplemental to the dictionary are a domain term list, a terminology dictionary, and a data model to help organize the concepts constituting the health statistics domain.
The Statistical Analysis of General Processing Tree Models with the EM Algorithm.
Hu, Xiangen; Batchelder, William H.
1994-01-01
The statistical analysis of processing tree models is advanced by showing how the parameters of estimation and hypothesis testing, based on the likelihood functions, can be accomplished by adapting the expectation-maximization (EM) algorithm. The adaptation makes it easy to program a personal computer to accomplish the stages of statistical…
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.
Statistical analysis of radial interface growth
International Nuclear Information System (INIS)
Masoudi, A A; Hosseinabadi, S; Khorrami, M; Davoudi, J; Kohandel, M
2012-01-01
Recent studies have questioned the application of standard scaling analysis to study radially growing interfaces (Escudero 2008 Phys. Rev. Lett. 100 116101; 2009 Ann. Phys. 324 1796). We show that the radial Edwards–Wilkinson (EW) equation belongs to the same universality as that obtained in the planar geometry. In addition, we use numerical simulations to calculate the interface width for both random deposition with surface relaxation (RDSR) and restricted solid on solid (RSOS) models, assuming that the system size increases linearly with time (due to radial geometry). By applying appropriate rules for each model, we show that the interface width increases with time as t β , where the exponent β is the same as those obtained from the corresponding planar geometries. (letter)
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.
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.
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 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.
statistical analysis of wind speed for electrical power generation
African Journals Online (AJOL)
HOD
Keywords: Wind speed - probability - density function – wind energy conversion system- statistical analyses. 1. INTRODUCTION. In order ..... "Statistical analysis of wind speed distribution based on six Weibull Methods for wind power evaluation in. Garoua, Cameroon," Revue des Energies. Renouvelables, vol. 18, no. 1, pp.
Statistical Compilation of the ICT Sector and Policy Analysis | IDRC ...
International Development Research Centre (IDRC) Digital Library (Canada)
Final technical report / statistical compilation of the ICT sector and policy analysis : a communication for development approach to scientific training and research and its extension digital transformations; seeking applied frameworks and indicators. Download PDF. Studies. Statistical Compilation of the ICT Sector and Policy ...
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
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
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.…
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.
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.
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.
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.
Directory of Open Access Journals (Sweden)
Yuan Fei
2007-02-01
Full Text Available Abstract Background In general, prognosis and impact of prognostic/predictive factors are assessed with Kaplan-Meier plots and/or the Cox proportional hazard model. There might be substantive differences from the results using these models for the same patients, if different statistical methods were used, for example, Boag log-normal (cure-rate model, or log-normal survival analysis. Methods Cohort of 244 limited-stage small-cell lung cancer patients, were accrued between 1981 and 1998, and followed to the end of 2005. The endpoint was death with or from lung cancer, for disease-specific survival (DSS. DSS at 1-, 3- and 5-years, with 95% confidence limits, are reported for all patients using the Boag, Kaplan-Meier, Cox, and log-normal survival analysis methods. Factors with significant effects on DSS were identified with step-wise forward multivariate Cox and log-normal survival analyses. Then, DSS was ascertained for patients with specific characteristics defined by these factors. Results The median follow-up of those alive was 9.5 years. The lack of events after 1966 days precluded comparison after 5 years. DSS assessed by the four methods in the full cohort differed by 0–2% at 1 year, 0–12% at 3 years, and 0–1% at 5 years. Log-normal survival analysis indicated DSS of 38% at 3 years, 10–12% higher than with other methods; univariate 95% confidence limits were non-overlapping. Surgical resection, hemoglobin level, lymph node involvement, and superior vena cava (SVC obstruction significantly impacted DSS. DSS assessed by the Cox and log-normal survival analysis methods for four clinical risk groups differed by 1–6% at 1 year, 15–26% at 3 years, and 0–12% at 5 years; multivariate 95% confidence limits were overlapping in all instances. Conclusion Surgical resection, hemoglobin level, lymph node involvement, and superior vena cava (SVC obstruction all significantly impacted DSS. Apparent DSS for patients was influenced by the
[Statistical analysis using freely-available "EZR (Easy R)" software].
Kanda, Yoshinobu
2015-10-01
Clinicians must often perform statistical analyses for purposes such evaluating preexisting evidence and designing or executing clinical studies. R is a free software environment for statistical computing. R supports many statistical analysis functions, but does not incorporate a statistical graphical user interface (GUI). The R commander provides an easy-to-use basic-statistics GUI for R. However, the statistical function of the R commander is limited, especially in the field of biostatistics. Therefore, the author added several important statistical functions to the R commander and named it "EZR (Easy R)", which is now being distributed on the following website: http://www.jichi.ac.jp/saitama-sct/. EZR allows the application of statistical functions that are frequently used in clinical studies, such as survival analyses, including competing risk analyses and the use of time-dependent covariates and so on, by point-and-click access. In addition, by saving the script automatically created by EZR, users can learn R script writing, maintain the traceability of the analysis, and assure that the statistical process is overseen by a supervisor.
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)
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
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
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 ...
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.
Statistical learning in specific language impairment : A meta-analysis
Lammertink, Imme; Boersma, Paul; Wijnen, Frank; Rispens, Judith
2017-01-01
Purpose: The current meta-analysis provides a quantitative overview of published and unpublished studies on statistical learning in the auditory verbal domain in people with and without specific language impairment (SLI). The database used for the meta-analysis is accessible online and open to
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 ...
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
Using multivariate statistical analysis to assess changes in water ...
African Journals Online (AJOL)
2000; Evans et al., 2001; Kernan and Helliwell, 2001; Wright et al., 2001 .... Statistical analysis was used to examine the water quality at the five sites for ... An analysis of covariance. (ANCOVA) was used to test for site (spatial) differences in water quality. To assess for differences between sites, the ANCOVA compared the ...
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...
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.
Skol, Andrew D; Scott, Laura J; Abecasis, Gonçalo R; Boehnke, Michael
2006-02-01
Genome-wide association is a promising approach to identify common genetic variants that predispose to human disease. Because of the high cost of genotyping hundreds of thousands of markers on thousands of subjects, genome-wide association studies often follow a staged design in which a proportion (pi(samples)) of the available samples are genotyped on a large number of markers in stage 1, and a proportion (pi(samples)) of these markers are later followed up by genotyping them on the remaining samples in stage 2. The standard strategy for analyzing such two-stage data is to view stage 2 as a replication study and focus on findings that reach statistical significance when stage 2 data are considered alone. We demonstrate that the alternative strategy of jointly analyzing the data from both stages almost always results in increased power to detect genetic association, despite the need to use more stringent significance levels, even when effect sizes differ between the two stages. We recommend joint analysis for all two-stage genome-wide association studies, especially when a relatively large proportion of the samples are genotyped in stage 1 (pi(samples) >or= 0.30), and a relatively large proportion of markers are selected for follow-up in stage 2 (pi(markers) >or= 0.01).
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...
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
Vibro-Acoustic Response Analysis Of LAUNCH VEHICLE INTER-STAGE
Directory of Open Access Journals (Sweden)
Anjana Mariam Alex
2015-08-01
Full Text Available Right from lift-off launch vehicles are subjected to extreme dynamic pressure aero and structure borne excitations. Inter-stage is fundamental to the vehicle as it houses the different control equipments actuators sensors motors and avionic packages. This paper involves the creation of two different models so as to study the correlation using two approaches Finite Element method and Hybrid Method involving Statistical Energy Analysis and Finite Element Analysis. The correlation of the response obtained on the Inter-stage from an acoustic ground test to that from the analytical test results carried out with VA One is also addressed in this paper.
Towards proper sampling and statistical analysis of defects
Directory of Open Access Journals (Sweden)
Cetin Ali
2014-06-01
Full Text Available Advancements in applied statistics with great relevance to defect sampling and analysis are presented. Three main issues are considered; (i proper handling of multiple defect types, (ii relating sample data originating from polished inspection surfaces (2D to finite material volumes (3D, and (iii application of advanced extreme value theory in statistical analysis of block maximum data. Original and rigorous, but practical mathematical solutions are presented. Finally, these methods are applied to make prediction regarding defect sizes in a steel alloy containing multiple defect types.
Adaptive strategy for the statistical analysis of connectomes.
Directory of Open Access Journals (Sweden)
Djalel Eddine Meskaldji
Full Text Available We study an adaptive statistical approach to analyze brain networks represented by brain connection matrices of interregional connectivity (connectomes. Our approach is at a middle level between a global analysis and single connections analysis by considering subnetworks of the global brain network. These subnetworks represent either the inter-connectivity between two brain anatomical regions or by the intra-connectivity within the same brain anatomical region. An appropriate summary statistic, that characterizes a meaningful feature of the subnetwork, is evaluated. Based on this summary statistic, a statistical test is performed to derive the corresponding p-value. The reformulation of the problem in this way reduces the number of statistical tests in an orderly fashion based on our understanding of the problem. Considering the global testing problem, the p-values are corrected to control the rate of false discoveries. Finally, the procedure is followed by a local investigation within the significant subnetworks. We contrast this strategy with the one based on the individual measures in terms of power. We show that this strategy has a great potential, in particular in cases where the subnetworks are well defined and the summary statistics are properly chosen. As an application example, we compare structural brain connection matrices of two groups of subjects with a 22q11.2 deletion syndrome, distinguished by their IQ scores.
Statistical margin to DNB safety analysis approach for LOFT
International Nuclear Information System (INIS)
Atkinson, S.A.
1982-01-01
A method was developed and used for LOFT thermal safety analysis to estimate the statistical margin to DNB for the hot rod, and to base safety analysis on desired DNB probability limits. This method is an advanced approach using response surface analysis methods, a very efficient experimental design, and a 2nd-order response surface equation with a 2nd-order error propagation analysis to define the MDNBR probability density function. Calculations for limiting transients were used in the response surface analysis thereby including transient interactions and trip uncertainties in the MDNBR probability density
Data analysis using the Gnu R system for statistical computation
Energy Technology Data Exchange (ETDEWEB)
Simone, James; /Fermilab
2011-07-01
R is a language system for statistical computation. It is widely used in statistics, bioinformatics, machine learning, data mining, quantitative finance, and the analysis of clinical drug trials. Among the advantages of R are: it has become the standard language for developing statistical techniques, it is being actively developed by a large and growing global user community, it is open source software, it is highly portable (Linux, OS-X and Windows), it has a built-in documentation system, it produces high quality graphics and it is easily extensible with over four thousand extension library packages available covering statistics and applications. This report gives a very brief introduction to R with some examples using lattice QCD simulation results. It then discusses the development of R packages designed for chi-square minimization fits for lattice n-pt correlation functions.
Karakatsanis, L. P.; Iliopoulos, A. C.; Pavlos, E. G.; Pavlos, G. P.
2018-02-01
In this paper, we perform statistical analysis of time series deriving from Earth's climate. The time series are concerned with Geopotential Height (GH) and correspond to temporal and spatial components of the global distribution of month average values, during the period (1948-2012). The analysis is based on Tsallis non-extensive statistical mechanics and in particular on the estimation of Tsallis' q-triplet, namely {qstat, qsens, qrel}, the reconstructed phase space and the estimation of correlation dimension and the Hurst exponent of rescaled range analysis (R/S). The deviation of Tsallis q-triplet from unity indicates non-Gaussian (Tsallis q-Gaussian) non-extensive character with heavy tails probability density functions (PDFs), multifractal behavior and long range dependences for all timeseries considered. Also noticeable differences of the q-triplet estimation found in the timeseries at distinct local or temporal regions. Moreover, in the reconstructive phase space revealed a lower-dimensional fractal set in the GH dynamical phase space (strong self-organization) and the estimation of Hurst exponent indicated multifractality, non-Gaussianity and persistence. The analysis is giving significant information identifying and characterizing the dynamical characteristics of the earth's climate.
Planning and Analysis swimmers training in the basic stage
Willner, Jiří
2013-01-01
Title: Planning and Analysis swimmers training in the basic stage Objectives: The aim is to experimentally apply an annual training plan developed based on previous training to a selected swimmers in the basic stage in given conditions. Subject to monitoring and recording are general indicators of training, diagnostic techniques swimming styles and selected functional indicators. Through track record at selected competitions we have verified the effectiveness and validity of the implemented p...
Orthopedic research: an overview of data entry, database management, and statistical analysis.
Kassing, D R; Ritter, M A; Faris, P M; Keating, E M; Nyhuis, A W
1989-12-01
An orthopedic practitioner can facilitate clinical research and analyze quality assurance data with a minor investment in a personal computer, an optical scanner, and two software packages, namely a database manager and a statistics program. One of the most time-consuming stages in the research process includes entering patient chart data, editing and manipulating the data (database management), and analyzing the data (statistical analysis). This can be automated to a large extent with the above mentioned equipment. This article focuses on the steps involved in organizing an orthopedic office for research. The steps include choosing a method of data entry, choosing and implementing a database package, and choosing and implementing a statistics package. This discussion is followed by a practical review of basic statistics applicable to orthopedic research. Several simple and advanced tests are described and examples are given for each.
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
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
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
da Silveira, Thiago L T; Kozakevicius, Alice J; Rodrigues, Cesar R
2017-02-01
The main objective of this study was to enhance the performance of sleep stage classification using single-channel electroencephalograms (EEGs), which are highly desirable for many emerging technologies, such as telemedicine and home care. The proposed method consists of decomposing EEGs by a discrete wavelet transform and computing the kurtosis, skewness and variance of its coefficients at selected levels. A random forest predictor is trained to classify each epoch into one of the Rechtschaffen and Kales' stages. By performing a comprehensive set of tests on 106,376 epochs available from the Physionet public database, it is demonstrated that the use of these three statistical moments has enhanced performance when compared to their application in the time domain. Furthermore, the chosen set of features has the advantage of exhibiting a stable classification performance for all scoring systems, i.e., from 2- to 6-state sleep stages. The stability of the feature set is confirmed with ReliefF tests which show a performance reduction when any individual feature is removed, suggesting that this group of feature cannot be further reduced. The accuracies and kappa coefficients yield higher than 90 % and 0.8, respectively, for all of the 2- to 6-state sleep stage classification cases.
Using multivariate statistical analysis to assess changes in water ...
African Journals Online (AJOL)
Multivariate statistical analysis was used to investigate changes in water chemistry at 5 river sites in the Vaal Dam catchment, draining the Highveld grasslands. These grasslands receive more than 8 kg sulphur (S) ha-1·year-1 and 6 kg nitrogen (N) ha-1·year-1 via atmospheric deposition. It was hypothesised that between ...
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 ...
Multiple defect distributions on weibull statistical analysis of fatigue ...
African Journals Online (AJOL)
By relaxing the assumptions of a single cast defect distribution, of uniformity throughout the material and of uniformity from specimen to specimen, Weibull statistical analysis for multiple defect distributions have been applied to correctly describe the fatigue life data of aluminium alloy castings having multiple cast defects ...
Toward a theory of statistical tree-shape analysis
DEFF Research Database (Denmark)
Feragen, Aasa; Lo, Pechin Chien Pau; de Bruijne, Marleen
2013-01-01
has nice geometric properties which are needed for statistical analysis: geodesics always exist, and are generically locally unique. Following this we can also show existence and generic local uniqueness of average trees for QED. TED, while having some algorithmic advantages, does not share...
French University Libraries 1988-1998: A Statistical Analysis
Directory of Open Access Journals (Sweden)
Gernot U. Gabel
2001-07-01
Full Text Available Based on an analysis of statistical data from the past decade which have been published annually by the French Ministry of Education (Annuaire des bibliothèques universitaires, the article gives an overview of developments with regard to buildings, personnel, services, acquisitions and collections of French university libraries during the last decade.
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 ...
Statistical analysis of thermal conductivity of nanofluid containing ...
Indian Academy of Sciences (India)
Abstract. In this paper, we report for the first time the statistical analysis of thermal conductivity of nanofluids containing TiO2 nanoparticles, pristine MWCNTs and decorated MWCNTs with different amounts of TiO2 nanoparticles. The functionalized MWCNT and synthesized hybrid of MWCNT–TiO2 were characterized using ...
Evaluation of Statistical Models for Analysis of Insect, Disease and ...
African Journals Online (AJOL)
It is concluded that LMMs and GLMs simultaneously consider the effect of treatments and heterogeneity of variance and hence are more appropriate for analysis of abundance and incidence data than ordinary ANOVA. Keywords: Mixed Models; Generalized Linear Models; Statistical Power East African Journal of Sciences ...
A Statistical Analysis of Women's Perceptions on Politics and Peace ...
African Journals Online (AJOL)
This article is a statistical analysis of the perception that more women in politics would enhance peace building. The data was drawn from a comparative survey of 325 women and four men (community leaders) in the regions of the Niger Delta (Nigeria) and KwaZulu-Natal (South Africa). According to the findings, the ...
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)
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.)
Statistical analysis of stretch film production process capabilities
Kovačić, Goran; Kondić, Živko
2012-01-01
The basic concept of statistical process control is based on the comparison of data collected from the process with calculated control limits and conclusions about the process based on the above. This process is recognized as a modern method for the analysis of process capabilities over different capability indexes. This paper describes the application of this method in monitoring and analysis of stretch film production process capabilities.
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.)
Bryan Mound SPR cavern 113 remedial leach stage 1 analysis.
Energy Technology Data Exchange (ETDEWEB)
Rudeen, David Keith; Weber, Paula D.; Lord, David L.
2013-08-01
The U.S. Strategic Petroleum Reserve implemented the first stage of a leach plan in 2011-2012 to expand storage volume in the existing Bryan Mound 113 cavern from a starting volume of 7.4 million barrels (MMB) to its design volume of 11.2 MMB. The first stage was terminated several months earlier than expected in August, 2012, as the upper section of the leach zone expanded outward more quickly than design. The oil-brine interface was then re-positioned with the intent to resume leaching in the second stage configuration. This report evaluates the as-built configuration of the cavern at the end of the first stage, and recommends changes to the second stage plan in order to accommodate for the variance between the first stage plan and the as-built cavern. SANSMIC leach code simulations are presented and compared with sonar surveys in order to aid in the analysis and offer projections of likely outcomes from the revised plan for the second stage leach.
Statistical analysis of absorptive laser damage in dielectric thin films
Energy Technology Data Exchange (ETDEWEB)
Budgor, A.B.; Luria-Budgor, K.F.
1978-09-11
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/sub 2/, ZrO/sub 2/, and Al/sub 2/O/sub 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.
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
Statistical analysis for coded aperture γ-ray telescope
International Nuclear Information System (INIS)
Ducros, G.; Ducros, R.
1984-01-01
We have developed a statistical analysis of the image recorded by a position sensitive detector associated with a coded mask for the French gamma ray satellite SIGMA, in the energy range (20-2 000 keV). The aperture of the telescope is not limited to the size of the mask. In the first part, we described the principle of the image analysis based on the least squares method with a fit function generated and tested term after term. The statistical test is performed on the F distribution followed by the relative improvement of chi 2 when the fit function has an additional term. The second part deals with digital processing aspects: the adjustment of the method to reduce computation time, and the analysis results of two simulated images. (orig.)
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.
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
SMART: Statistical Metabolomics Analysis-An R Tool.
Liang, Yu-Jen; Lin, Yu-Ting; Chen, Chia-Wei; Lin, Chien-Wei; Chao, Kun-Mao; Pan, Wen-Harn; Yang, Hsin-Chou
2016-06-21
Metabolomics data provide unprecedented opportunities to decipher metabolic mechanisms by analyzing hundreds to thousands of metabolites. Data quality concerns and complex batch effects in metabolomics must be appropriately addressed through statistical analysis. This study developed an integrated analysis tool for metabolomics studies to streamline the complete analysis flow from initial data preprocessing to downstream association analysis. We developed Statistical Metabolomics Analysis-An R Tool (SMART), which can analyze input files with different formats, visually represent various types of data features, implement peak alignment and annotation, conduct quality control for samples and peaks, explore batch effects, and perform association analysis. A pharmacometabolomics study of antihypertensive medication was conducted and data were analyzed using SMART. Neuromedin N was identified as a metabolite significantly associated with angiotensin-converting-enzyme inhibitors in our metabolome-wide association analysis (p = 1.56 × 10(-4) in an analysis of covariance (ANCOVA) with an adjustment for unknown latent groups and p = 1.02 × 10(-4) in an ANCOVA with an adjustment for hidden substructures). This endogenous neuropeptide is highly related to neurotensin and neuromedin U, which are involved in blood pressure regulation and smooth muscle contraction. The SMART software, a user guide, and example data can be downloaded from http://www.stat.sinica.edu.tw/hsinchou/metabolomics/SMART.htm .
Higher Education in Persons with Disabilities: Statistical Analysis
Directory of Open Access Journals (Sweden)
Arzhanykh E.V.,
2017-08-01
Full Text Available The paper presents statistical research data on teaching/learning in individuals with disabilities enrolled in higher education programmes. The analysis is based on the information drawn from a statistical form VPO-1 “Information on educational organization offering bachelor’s, master’s and specialist programmes in higher education”. The following indicators were analysed: the dynamics of the number of students with disabilities studying at universities; distribution of students according to the level of higher education and the type of their disability; distribution of students according to the chosen profession; and the data collected in the Russian regions. The paper concludes that even though the available statistical data do not allow for a full complex exploration into the subject of higher education in students with disabilities, the scope of the accessible information is reasonably wide.
Statistical analysis of surgical pathology data using the R program.
Cuff, Justin; Higgins, John P T
2012-05-01
An understanding of statistics is essential for analysis of many types of data including data sets typically reported in surgical pathology research papers. Fortunately, a relatively small number of statistical tests apply to data relevant to surgical pathologists. An understanding of when to apply these tests would greatly benefit surgical pathologists who read and/or write papers. In this review, we show how the publicly available statistical program R can be used to analyze recently published surgical pathology papers to replicate the p-values and survival curves presented in these papers. Areas covered include: T-test, chi-square and Fisher exact tests of proportionality, Kaplan-Meier survival curves, the log rank test, and Cox proportional hazards.
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
Software for statistical data analysis used in Higgs searches
International Nuclear Information System (INIS)
Gumpert, Christian; Moneta, Lorenzo; Cranmer, Kyle; Kreiss, Sven; Verkerke, Wouter
2014-01-01
The analysis and interpretation of data collected by the Large Hadron Collider (LHC) requires advanced statistical tools in order to quantify the agreement between observation and theoretical models. RooStats is a project providing a statistical framework for data analysis with the focus on discoveries, confidence intervals and combination of different measurements in both Bayesian and frequentist approaches. It employs the RooFit data modelling language where mathematical concepts such as variables, (probability density) functions and integrals are represented as C++ objects. RooStats and RooFit rely on the persistency technology of the ROOT framework. The usage of a common data format enables the concept of digital publishing of complicated likelihood functions. The statistical tools have been developed in close collaboration with the LHC experiments to ensure their applicability to real-life use cases. Numerous physics results have been produced using the RooStats tools, with the discovery of the Higgs boson by the ATLAS and CMS experiments being certainly the most popular among them. We will discuss tools currently used by LHC experiments to set exclusion limits, to derive confidence intervals and to estimate discovery significances based on frequentist statistics and the asymptotic behaviour of likelihood functions. Furthermore, new developments in RooStats and performance optimisation necessary to cope with complex models depending on more than 1000 variables will be reviewed
Statistical 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 Modeling of CTV Motion and Deformation for IMRT of Early-Stage Rectal Cancer
Energy Technology Data Exchange (ETDEWEB)
Bondar, Luiza, E-mail: M.L.Bondar@umcutrecht.nl [Department of Radiotherapy, University Medical Center Utrecht, Utrecht (Netherlands); Intven, Martijn; Burbach, J.P. Maarten [Department of Radiotherapy, University Medical Center Utrecht, Utrecht (Netherlands); Budiarto, Eka [Delft Institute of Applied Mathematics, Delft University of Technology, Delft (Netherlands); Kleijnen, Jean-Paul; Philippens, Marielle; Asselen, Bram van; Seravalli, Enrica; Reerink, Onne; Raaymakers, Bas [Department of Radiotherapy, University Medical Center Utrecht, Utrecht (Netherlands)
2014-11-01
Purpose: To derive and validate a statistical model of motion and deformation for the clinical target volume (CTV) of early-stage rectal cancer patients. Methods and Materials: For 16 patients, 4 to 5 magnetic resonance images (MRI) were acquired before each fraction was administered. The CTV was delineated on each MRI. Using a leave-one-out methodology, we constructed a population-based principal component analysis (PCA) model of the CTV motion and deformation of 15 patients, and we tested the model on the left-out patient. The modeling error was calculated as the amount of the CTV motion-deformation of the left-out-patient that could not be explained by the PCA model. Next, the PCA model was used to construct a PCA target volume (PCA-TV) by accumulating motion-deformations simulated by the model. A PCA planning target volume (PTV) was generated by expanding the PCA-TV by uniform margins. The PCA-PTV was compared with uniform and nonuniform CTV-to-PTV margins. To allow comparison, geometric margins were determined to ensure adequate coverage, and the volume difference between the PTV and the daily CTV (CTV-to-PTV volume) was calculated. Results: The modeling error ranged from 0.9 ± 0.5 to 2.9 ± 2.1 mm, corresponding to a reduction of the CTV motion-deformation between 6% and 60% (average, 23% ± 11%). The reduction correlated with the magnitude of the CTV motion-deformation (P<.001, R=0.66). The PCA-TV and the CTV required 2-mm and 7-mm uniform margins, respectively. The nonuniform CTV-to-PTV margins were 4 mm in the left, right, inferior, superior, and posterior directions and 8 mm in the anterior direction. Compared to uniform and nonuniform CTV-to-PTV margins, the PCA-based PTV significantly decreased (P<.001) the average CTV-to-PTV volume by 128 ± 20 mL (49% ± 4%) and by 35 ± 6 mL (20% ± 3.5%), respectively. Conclusions: The CTV motion-deformation of a new patient can be explained by a population-based PCA model. A PCA model
Collagen morphology and texture analysis: from statistics to classification
Mostaço-Guidolin, Leila B.; Ko, Alex C.-T.; Wang, Fei; Xiang, Bo; Hewko, Mark; Tian, Ganghong; Major, Arkady; Shiomi, Masashi; Sowa, Michael G.
2013-07-01
In this study we present an image analysis methodology capable of quantifying morphological changes in tissue collagen fibril organization caused by pathological conditions. Texture analysis based on first-order statistics (FOS) and second-order statistics such as gray level co-occurrence matrix (GLCM) was explored to extract second-harmonic generation (SHG) image features that are associated with the structural and biochemical changes of tissue collagen networks. Based on these extracted quantitative parameters, multi-group classification of SHG images was performed. With combined FOS and GLCM texture values, we achieved reliable classification of SHG collagen images acquired from atherosclerosis arteries with >90% accuracy, sensitivity and specificity. The proposed methodology can be applied to a wide range of conditions involving collagen re-modeling, such as in skin disorders, different types of fibrosis and muscular-skeletal diseases affecting ligaments and cartilage.
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.
GNSS Spoofing Detection Based on Signal Power Measurements: Statistical Analysis
Directory of Open Access Journals (Sweden)
V. Dehghanian
2012-01-01
Full Text Available A threat to GNSS receivers is posed by a spoofing transmitter that emulates authentic signals but with randomized code phase and Doppler values over a small range. Such spoofing signals can result in large navigational solution errors that are passed onto the unsuspecting user with potentially dire consequences. An effective spoofing detection technique is developed in this paper, based on signal power measurements and that can be readily applied to present consumer grade GNSS receivers with minimal firmware changes. An extensive statistical analysis is carried out based on formulating a multihypothesis detection problem. Expressions are developed to devise a set of thresholds required for signal detection and identification. The detection processing methods developed are further manipulated to exploit incidental antenna motion arising from user interaction with a GNSS handheld receiver to further enhance the detection performance of the proposed algorithm. The statistical analysis supports the effectiveness of the proposed spoofing detection technique under various multipath conditions.
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.
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%.
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.
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...
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 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
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 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
Analysis of spectral data with rare events statistics
International Nuclear Information System (INIS)
Ilyushchenko, V.I.; Chernov, N.I.
1990-01-01
The case is considered of analyzing experimental data, when the results of individual experimental runs cannot be summed due to large systematic errors. A statistical analysis of the hypothesis about the persistent peaks in the spectra has been performed by means of the Neyman-Pearson test. The computations demonstrate the confidence level for the hypothesis about the presence of a persistent peak in the spectrum is proportional to the square root of the number of independent experimental runs, K. 5 refs
Statistical 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.
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....
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
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.
HistFitter: a flexible framework for statistical data analysis
Besjes, G J; Côté, D; Koutsman, A; Lorenz, J M; Short, D
2015-01-01
HistFitter is a software framework for statistical data analysis that has been used extensively in the ATLAS Collaboration to analyze data of proton-proton collisions produced by the Large Hadron Collider at CERN. Most notably, HistFitter has become a de-facto standard in searches for supersymmetric particles since 2012, with some usage for Exotic and Higgs boson physics. HistFitter coherently combines several statistics tools in a programmable and flexible framework that is capable of bookkeeping hundreds of data models under study using thousands of generated input histograms.HistFitter interfaces with the statistics tools HistFactory and RooStats to construct parametric models and to perform statistical tests of the data, and extends these tools in four key areas. The key innovations are to weave the concepts of control, validation and signal regions into the very fabric of HistFitter, and to treat these with rigorous methods. Multiple tools to visualize and interpret the results through a simple configura...
A Laboratory Exercise in Statistical Analysis of Data
Vitha, Mark F.; Carr, Peter W.
1997-08-01
An undergraduate laboratory exercise in statistical analysis of data has been developed based on facile weighings of vitamin E pills. The use of electronic top-loading balances allows for very rapid data collection. Therefore, students obtain a sufficiently large number of replicates to provide statistically meaningful data sets. Through this exercise, students explore the effects of sample size and different types of sample averaging on the standard deviation of the average weight per pill. An emphasis is placed on the difference between the standard deviation of the mean and the standard deviation of the population. Students also perform the Q-test and t-test and are introduced to the X2-test. In this report, the class data from two consecutive offerings of the course are compared and reveal a statistically significant increase in the average weight per pill, presumably due to the absorption of water over time. Histograms of the class data are shown and used to illustrate the importance of plotting the data. Overall, through this brief laboratory exercise, students are exposed to many important statistical tests and concepts which are then used and further developed throughout the remainder of the course.
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).
Renal cell cancer stage migration: analysis of the National Cancer Data Base.
Kane, Christopher J; Mallin, Katherine; Ritchey, Jamie; Cooperberg, Matthew R; Carroll, Peter R
2008-07-01
Evidence exists to suggest a pattern of increasing early diagnosis of renal cell carcinoma (RCC). The aim of the study was to analyze patterns of disease presentation and outcome of RCC by AJCC stage using data from the National Cancer Data Base (NCDB) over a 12-year period. The NCDB was queried for adults diagnosed between 1993 and 2004 presenting with ICD-O-2 of 3 renal cell tumors arising in the kidney. Cases were classified by demographics, 2002 AJCC stage (6th edition), and histology. The Cochran-Armitage Test for Trend was used to determine statistical significance of trends over time. Cox regression multivariate analysis was used to evaluate the impact of stage and histology on relative survival. SPSS 14.0 was used for analyses. Between 1993 and 2004 a total of 205,963 patients from the NCDB fit our case definition of RCC. Comparisons between 1993 and 2004 data show an increase in stage I disease and decrease in stage II, III, and IV disease (P < or = .001). The size of stage I tumors also decreased from a mean of 4.1 cm in 1993 to 3.6 cm in 2003. In multivariate analysis, stage, but not histology, predicted relative survival. A 3.3% increase in survival was found for patients diagnosed in 1998 compared with patients diagnosed in 1993. A greater proportion of newly diagnosed patients with RCC currently present with stage I disease compared with earlier years. Stage predicts relative survival for patients with kidney cancer. More recently diagnosed patients have improved relative survival. (Copyright) 2008 American Cancer Society.
Metz, Anneke M
2008-01-01
There is an increasing need for students in the biological sciences to build a strong foundation in quantitative approaches to data analyses. Although most science, engineering, and math field majors are required to take at least one statistics course, statistical analysis is poorly integrated into undergraduate biology course work, particularly at the lower-division level. Elements of statistics were incorporated into an introductory biology course, including a review of statistics concepts and opportunity for students to perform statistical analysis in a biological context. Learning gains were measured with an 11-item statistics learning survey instrument developed for the course. Students showed a statistically significant 25% (p biology. Students improved their scores on the survey after completing introductory biology, even if they had previously completed an introductory statistics course (9%, improvement p biology showed no loss of their statistics knowledge as measured by this instrument, suggesting that the use of statistics in biology course work may aid long-term retention of statistics knowledge. No statistically significant differences in learning were detected between male and female students in the study.
The Effects of Statistical Analysis Software and Calculators on Statistics Achievement
Christmann, Edwin P.
2009-01-01
This study compared the effects of microcomputer-based statistical software and hand-held calculators on the statistics achievement of university males and females. The subjects, 73 graduate students enrolled in univariate statistics classes at a public comprehensive university, were randomly assigned to groups that used either microcomputer-based…
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 ...
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 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 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 analysis of nanoparticle dosing in a dynamic cellular system.
Summers, Huw D; Rees, Paul; Holton, Mark D; Brown, M Rowan; Chappell, Sally C; Smith, Paul J; Errington, Rachel J
2011-03-01
The delivery of nanoparticles into cells is important in therapeutic applications and in nanotoxicology. Nanoparticles are generally targeted to receptors on the surfaces of cells and internalized into endosomes by endocytosis, but the kinetics of the process and the way in which cell division redistributes the particles remain unclear. Here we show that the chance of success or failure of nanoparticle uptake and inheritance is random. Statistical analysis of nanoparticle-loaded endosomes indicates that particle capture is described by an over-dispersed Poisson probability distribution that is consistent with heterogeneous adsorption and internalization. Partitioning of nanoparticles in cell division is random and asymmetric, following a binomial distribution with mean probability of 0.52-0.72. These results show that cellular targeting of nanoparticles is inherently imprecise due to the randomness of nature at the molecular scale, and the statistical framework offers a way to predict nanoparticle dosage for therapy and for the study of nanotoxins.
Statistical analysis of effective singular values in matrix rank determination
Konstantinides, Konstantinos; Yao, Kung
1988-01-01
A major problem in using SVD (singular-value decomposition) as a tool in determining the effective rank of a perturbed matrix is that of distinguishing between significantly small and significantly large singular values to the end, conference regions are derived for the perturbed singular values of matrices with noisy observation data. The analysis is based on the theories of perturbations of singular values and statistical significance test. Threshold bounds for perturbation due to finite-precision and i.i.d. random models are evaluated. In random models, the threshold bounds depend on the dimension of the matrix, the noisy variance, and predefined statistical level of significance. Results applied to the problem of determining the effective order of a linear autoregressive system from the approximate rank of a sample autocorrelation matrix are considered. Various numerical examples illustrating the usefulness of these bounds and comparisons to other previously known approaches are given.
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).
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).
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.
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
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......, and the formulation and solution of an MINLP problem to identify the optimal processing route for multiple raw materials and products. Finally, economic, sustainability and LCA analysis are performed....
Composition and Statistical Analysis of Biophenols in Apulian Italian EVOOs.
Ragusa, Andrea; Centonze, Carla; Grasso, Maria Elena; Latronico, Maria Francesca; Mastrangelo, Pier Francesco; Fanizzi, Francesco Paolo; Maffia, Michele
2017-10-18
Extra-virgin olive oil (EVOO) is among the basic constituents of the Mediterranean diet. Its nutraceutical properties are due mainly, but not only, to a plethora of molecules with antioxidant activity known as biophenols. In this article, several biophenols were measured in EVOOs from South Apulia, Italy. Hydroxytyrosol, tyrosol and their conjugated structures to elenolic acid in different forms were identified and quantified by high performance liquid chromatography (HPLC) together with lignans, luteolin and α-tocopherol. The concentration of the analyzed metabolites was quite high in all the cultivars studied, but it was still possible to discriminate them through multivariate statistical analysis (MVA). Furthermore, principal component analysis (PCA) and orthogonal partial least-squares discriminant analysis (OPLS-DA) were also exploited for determining variances among samples depending on the interval time between harvesting and milling, on the age of the olive trees, and on the area where the olive trees were grown.
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.
Statistical analysis of C/NOFS planar Langmuir probe data
Directory of Open Access Journals (Sweden)
E. Costa
2014-07-01
Full Text Available The planar Langmuir probe (PLP onboard the Communication/Navigation Outage Forecasting System (C/NOFS satellite has been monitoring ionospheric plasma densities and their irregularities with high resolution almost seamlessly since May 2008. Considering the recent changes in status of the C/NOFS mission, it may be interesting to summarize some statistical results from these measurements. PLP data from 2 different years (1 October 2008–30 September 2009 and 1 January 2012–31 December 2012 were selected for analysis. The first data set corresponds to solar minimum conditions and the second one is as close to solar maximum conditions of solar cycle 24 as possible at the time of the analysis. The results from the analysis show how the values of the standard deviation of the ion density which are greater than specified thresholds are statistically distributed as functions of several combinations of the following geophysical parameters: (i solar activity, (ii altitude range, (iii longitude sector, (iv local time interval, (v geomagnetic latitude interval, and (vi season.
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.
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 muscle contraction based on MR images
International Nuclear Information System (INIS)
Horio, Hideyuki; Kuroda, Yoshihiro; Imura, Masataka; Oshiro, Osamu
2011-01-01
The purpose of this study was to distinguish the changes of MR signals during relaxation and contraction of muscles. First, MR images were acquired in relaxation and contraction states. The subject clasped his hands in relaxation state and unclasped in contraction state. Next, the images were segmented using mixture Gaussian distributions and expectation-maximization (EM) algorithm. Finally, we evaluated statistical values gotten from mixture Gaussian distributions. As a result, mixing coefficients were different during relaxation and contraction. The experimental results indicated that the proposed analysis has the potential to discriminate between two states. (author)
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
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
SAS and R data management, statistical analysis, and graphics
Kleinman, Ken
2014-01-01
An Up-to-Date, All-in-One Resource for Using SAS and R to Perform Frequent TasksThe first edition of this popular guide provided a path between SAS and R using an easy-to-understand, dictionary-like approach. Retaining the same accessible format, SAS and R: Data Management, Statistical Analysis, and Graphics, Second Edition explains how to easily 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, inferentia
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
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
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.
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
Multigene methylation analysis for detection and staging of prostate cancer.
Enokida, Hideki; Shiina, Hiroaki; Urakami, Shinji; Igawa, Mikio; Ogishima, Tatsuya; Li, Long-Cheng; Kawahara, Motoshi; Nakagawa, Masayuki; Kane, Christopher J; Carroll, Peter R; Dahiya, Rajvir
2005-09-15
Aberrant gene promoter methylation profiles have been well-studied in human prostate cancer. Therefore, we rationalize that multigene methylation analysis could be useful as a diagnostic biomarker. We hypothesize that a new method of multigene methylation analysis could be a good diagnostic and staging biomarker for prostate cancer. To test our hypothesis, prostate cancer samples (170) and benign prostatic hyperplasia samples (69) were examined by methylation-specific PCR for three genes: adenomatous polyposis coli (APC), glutathione S-transferase pi (GSTP1), and multidrug resistance 1 (MDR1). The methylation status of representative samples was confirmed by bisulfite DNA sequencing analysis. We further investigated whether methylation score (M score) can be used as a diagnostic and staging biomarker for prostate cancer. The M score of each sample was calculated as the sum of the corresponding log hazard ratio coefficients derived from multivariate logistic regression analysis of methylation status of various genes for benign prostatic hyperplasia and prostate cancer. The optimal sensitivity and specificity of the M score for diagnosis and for staging of prostate cancer was determined by receiver-operator characteristic (ROC) curve analysis. A pairwise comparison was employed to test for significance using the area under the ROC curve analysis. For each clinicopathologic finding, the association with prostate-specific antigen (PSA) failure-free probability was determined using Kaplan-Meier curves and a log-rank test was used to determine significance. The relationship between M score and clinicopathologic findings was analyzed by either the Mann-Whitney U test, Kruskal-Wallis test, or the Spearman rank correlation test. The frequency of positive methylation-specific PCR bands for APC, GSTP1, and MDR1 genes in prostate cancer samples was 64.1%, 54.0%, and 55.3%, respectively. In benign prostatic hyperplasia samples, it was 8.7%, 5.8%, and 11.6%, respectively. There
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.
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)
Image analysis and statistical inference in neuroimaging with R.
Tabelow, K; Clayden, J D; de Micheaux, P Lafaye; Polzehl, J; Schmid, V J; Whitcher, B
2011-04-15
R is a language and environment for statistical computing and graphics. It can be considered an alternative implementation of the S language developed in the 1970s and 1980s for data analysis and graphics (Becker and Chambers, 1984; Becker et al., 1988). The R language is part of the GNU project and offers versions that compile and run on almost every major operating system currently available. We highlight several R packages built specifically for the analysis of neuroimaging data in the context of functional MRI, diffusion tensor imaging, and dynamic contrast-enhanced MRI. We review their methodology and give an overview of their capabilities for neuroimaging. In addition we summarize some of the current activities in the area of neuroimaging software development in R. Copyright © 2011 Elsevier Inc. All rights reserved.
Statistical learning analysis in neuroscience: aiming for transparency.
Hanke, Michael; Halchenko, Yaroslav O; Haxby, James V; Pollmann, Stefan
2010-01-01
Encouraged by a rise of reciprocal interest between the machine learning and neuroscience communities, several recent studies have demonstrated the explanatory power of statistical learning techniques for the analysis of neural data. In order to facilitate a wider adoption of these methods, neuroscientific research needs to ensure a maximum of transparency to allow for comprehensive evaluation of the employed procedures. We argue that such transparency requires "neuroscience-aware" technology for the performance of multivariate pattern analyses of neural data that can be documented in a comprehensive, yet comprehensible way. Recently, we introduced PyMVPA, a specialized Python framework for machine learning based data analysis that addresses this demand. Here, we review its features and applicability to various neural data modalities.
Statistical learning analysis in neuroscience: aiming for transparency
Directory of Open Access Journals (Sweden)
Michael Hanke
2010-05-01
Full Text Available Encouraged by a rise of reciprocal interest between the machine learning and neuroscience communities, several recent studies have demonstrated the explanatory power of statistical learning techniques for the analysis of neural data. In order to facilitate a wider adoption of these methods neuroscientific research needs to ensure a maximum of transparency to allow for comprehensive evaluation of the employed procedures. We argue that such transparency requires ``neuroscience-aware'' technology for the performance of multivariate pattern analyses of neural data that can be documented in a comprehensive, yet comprehensible way. Recently, we introduced PyMVPA, a specialized Python framework for machine learning based data analysis that addresses this demand. Here we review its features and applicability to various neural data modalities.
Pattern recognition in menstrual bleeding diaries by statistical cluster analysis
Directory of Open Access Journals (Sweden)
Wessel Jens
2009-07-01
Full Text Available Abstract Background The aim of this paper is to empirically identify a treatment-independent statistical method to describe clinically relevant bleeding patterns by using bleeding diaries of clinical studies on various sex hormone containing drugs. Methods We used the four cluster analysis methods single, average and complete linkage as well as the method of Ward for the pattern recognition in menstrual bleeding diaries. The optimal number of clusters was determined using the semi-partial R2, the cubic cluster criterion, the pseudo-F- and the pseudo-t2-statistic. Finally, the interpretability of the results from a gynecological point of view was assessed. Results The method of Ward yielded distinct clusters of the bleeding diaries. The other methods successively chained the observations into one cluster. The optimal number of distinctive bleeding patterns was six. We found two desirable and four undesirable bleeding patterns. Cyclic and non cyclic bleeding patterns were well separated. Conclusion Using this cluster analysis with the method of Ward medications and devices having an impact on bleeding can be easily compared and categorized.
Statistical mechanical analysis of LMFBR fuel cladding tubes
International Nuclear Information System (INIS)
Poncelet, J.-P.; Pay, A.
1977-01-01
The most important design requirement on fuel pin cladding for LMFBR's is its mechanical integrity. Disruptive factors include internal pressure from mixed oxide fuel fission gas release, thermal stresses and high temperature creep, neutron-induced differential void-swelling as a source of stress in the cladding and irradiation creep of stainless steel material, corrosion by fission products. Under irradiation these load-restraining mechanisms are accentuated by stainless steel embrittlement and strength alterations. To account for the numerous uncertainties involved in the analysis by theoretical models and computer codes statistical tools are unavoidably requested, i.e. Monte Carlo simulation methods. Thanks to these techniques, uncertainties in nominal characteristics, material properties and environmental conditions can be linked up in a correct way and used for a more accurate conceptual design. First, a thermal creep damage index is set up through a sufficiently sophisticated clad physical analysis including arbitrary time dependence of power and neutron flux as well as effects of sodium temperature, burnup and steel mechanical behavior. Although this strain limit approach implies a more general but time consuming model., on the counterpart the net output is improved and e.g. clad temperature, stress and strain maxima may be easily assessed. A full spectrum of variables are statistically treated to account for their probability distributions. Creep damage probability may be obtained and can contribute to a quantitative fuel probability estimation
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.
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.
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
Statistical Models and Methods for Network Meta-Analysis.
Madden, L V; Piepho, H-P; Paul, P A
2016-08-01
Meta-analysis, the methodology for analyzing the results from multiple independent studies, has grown tremendously in popularity over the last four decades. Although most meta-analyses involve a single effect size (summary result, such as a treatment difference) from each study, there are often multiple treatments of interest across the network of studies in the analysis. Multi-treatment (or network) meta-analysis can be used for simultaneously analyzing the results from all the treatments. However, the methodology is considerably more complicated than for the analysis of a single effect size, and there have not been adequate explanations of the approach for agricultural investigations. We review the methods and models for conducting a network meta-analysis based on frequentist statistical principles, and demonstrate the procedures using a published multi-treatment plant pathology data set. A major advantage of network meta-analysis is that correlations of estimated treatment effects are automatically taken into account when an appropriate model is used. Moreover, treatment comparisons may be possible in a network meta-analysis that are not possible in a single study because all treatments of interest may not be included in any given study. We review several models that consider the study effect as either fixed or random, and show how to interpret model-fitting output. We further show how to model the effect of moderator variables (study-level characteristics) on treatment effects, and present one approach to test for the consistency of treatment effects across the network. Online supplemental files give explanations on fitting the network meta-analytical models using SAS.
Short-run and Current Analysis Model in Statistics
Directory of Open Access Journals (Sweden)
Constantin Anghelache
2006-01-01
Full Text Available Using the short-run statistic indicators is a compulsory requirement implied in the current analysis. Therefore, there is a system of EUROSTAT indicators on short run which has been set up in this respect, being recommended for utilization by the member-countries. On the basis of these indicators, there are regular, usually monthly, analysis being achieved in respect of: the production dynamic determination; the evaluation of the short-run investment volume; the development of the turnover; the wage evolution: the employment; the price indexes and the consumer price index (inflation; the volume of exports and imports and the extent to which the imports are covered by the exports and the sold of trade balance. The EUROSTAT system of indicators of conjuncture is conceived as an open system, so that it can be, at any moment extended or restricted, allowing indicators to be amended or even removed, depending on the domestic users requirements as well as on the specific requirements of the harmonization and integration. For the short-run analysis, there is also the World Bank system of indicators of conjuncture, which is utilized, relying on the data sources offered by the World Bank, The World Institute for Resources or other international organizations statistics. The system comprises indicators of the social and economic development and focuses on the indicators for the following three fields: human resources, environment and economic performances. At the end of the paper, there is a case study on the situation of Romania, for which we used all these indicators.
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
Statistical analysis and Kalman filtering applied to nuclear materials accountancy
International Nuclear Information System (INIS)
Annibal, P.S.
1990-08-01
Much theoretical research has been carried out on the development of statistical methods for nuclear material accountancy. In practice, physical, financial and time constraints mean that the techniques must be adapted to give an optimal performance in plant conditions. This thesis aims to bridge the gap between theory and practice, to show the benefits to be gained from a knowledge of the facility operation. Four different aspects are considered; firstly, the use of redundant measurements to reduce the error on the estimate of the mass of heavy metal in an 'accountancy tank' is investigated. Secondly, an analysis of the calibration data for the same tank is presented, establishing bounds for the error and suggesting a means of reducing them. Thirdly, a plant-specific method of producing an optimal statistic from the input, output and inventory data, to help decide between 'material loss' and 'no loss' hypotheses, is developed and compared with existing general techniques. Finally, an application of the Kalman Filter to materials accountancy is developed, to demonstrate the advantages of state-estimation techniques. The results of the analyses and comparisons illustrate the importance of taking into account a complete and accurate knowledge of the plant operation, measurement system, and calibration methods, to derive meaningful results from statistical tests on materials accountancy data, and to give a better understanding of critical random and systematic error sources. The analyses were carried out on the head-end of the Fast Reactor Reprocessing Plant, where fuel from the prototype fast reactor is cut up and dissolved. However, the techniques described are general in their application. (author)
Using robust statistics to improve neutron activation analysis results
International Nuclear Information System (INIS)
Zahn, Guilherme S.; Genezini, Frederico A.; Ticianelli, Regina B.; Figueiredo, Ana Maria G.
2011-01-01
Neutron activation analysis (NAA) is an analytical technique where an unknown sample is submitted to a neutron flux in a nuclear reactor, and its elemental composition is calculated by measuring the induced activity produced. By using the relative NAA method, one or more well-characterized samples (usually certified reference materials - CRMs) are irradiated together with the unknown ones, and the concentration of each element is then calculated by comparing the areas of the gamma ray peaks related to that element. When two or more CRMs are used as reference, the concentration of each element can be determined by several different ways, either using more than one gamma ray peak for that element (when available), or using the results obtained in the comparison with each CRM. Therefore, determining the best estimate for the concentration of each element in the sample can be a delicate issue. In this work, samples from three CRMs were irradiated together and the elemental concentration in one of them was calculated using the other two as reference. Two sets of peaks were analyzed for each element: a smaller set containing only the literature-recommended gamma-ray peaks and a larger one containing all peaks related to that element that could be quantified in the gamma-ray spectra; the most recommended transition was also used as a benchmark. The resulting data for each element was then reduced using up to five different statistical approaches: the usual (and not robust) unweighted and weighted means, together with three robust means: the Limitation of Relative Statistical Weight, Normalized Residuals and Rajeval. The resulting concentration values were then compared to the certified value for each element, allowing for discussion on both the performance of each statistical tool and on the best choice of peaks for each element. (author)
Directory of Open Access Journals (Sweden)
Browning Brian L
2008-07-01
Full Text Available Abstract Background Large-scale genetic association studies can test hundreds of thousands of genetic markers for association with a trait. Since the genetic markers may be correlated, a Bonferroni correction is typically too stringent a correction for multiple testing. Permutation testing is a standard statistical technique for determining statistical significance when performing multiple correlated tests for genetic association. However, permutation testing for large-scale genetic association studies is computationally demanding and calls for optimized algorithms and software. PRESTO is a new software package for genetic association studies that performs fast computation of multiple-testing adjusted P-values via permutation of the trait. Results PRESTO is an order of magnitude faster than other existing permutation testing software, and can analyze a large genome-wide association study (500 K markers, 5 K individuals, 1 K permutations in approximately one hour of computing time. PRESTO has several unique features that are useful in a wide range of studies: it reports empirical null distributions for the top-ranked statistics (i.e. order statistics, it performs user-specified combinations of allelic and genotypic tests, it performs stratified analysis when sampled individuals are from multiple populations and each individual's population of origin is specified, and it determines significance levels for one and two-stage genotyping designs. PRESTO is designed for case-control studies, but can also be applied to trio data (parents and affected offspring if transmitted parental alleles are coded as case alleles and untransmitted parental alleles are coded as control alleles. Conclusion PRESTO is a platform-independent software package that performs fast and flexible permutation testing for genetic association studies. The PRESTO executable file, Java source code, example data, and documentation are freely available at http://www.stat.auckland.ac.nz/~browning/presto/presto.html.
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.
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.
Cross-View Neuroimage Pattern Analysis for Alzheimer's Disease Staging
Directory of Open Access Journals (Sweden)
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.
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.
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 Distribution Analysis of Lineated Bands on Europa
Chen, T.; Phillips, C. B.; Pappalardo, R. T.
2016-12-01
Tina Chen, Cynthia B. Phillips, Robert T. Pappalardo Europa's surface is covered with intriguing linear and disrupted features, including lineated bands that range in scale and size. Previous studies have shown the possibility of an icy shell at the surface that may be concealing a liquid ocean with the potential to harboring life (Pappalardo et al., 1999). Utilizing the high-resolution imaging data from the Galileo spacecraft, we examined bands through a morphometric and morphologic approach. Greeley et al. (2000) and Procktor et al. (2002) have defined bands as wide, hummocky to lineated features that have distinctive surface texture and albedo compared to its surrounding terrain. We took morphometric measurements of lineated bands to find correlations in properties such as size, location, and orientation, and to shed light on formation models. We will present our measurements of over 100 bands on Europa that was mapped on the USGS Europa Global Mosaic Base Map (2002). We also conducted a statistical analysis to understand the distribution of lineated bands globally, and whether the widths of the bands differ by location. Our preliminary analysis from our statistical distribution evaluation, combined with the morphometric measurements, supports a uniform ice shell thickness for Europa rather than one that varies geographically. References: Greeley, Ronald, et al. "Geologic mapping of Europa." Journal of Geophysical Research: Planets 105.E9 (2000): 22559-22578.; Pappalardo, R. T., et al. "Does Europa have a subsurface ocean? Evaluation of the geological evidence." Journal of Geophysical Research: Planets 104.E10 (1999): 24015-24055.; Prockter, Louise M., et al. "Morphology of Europan bands at high resolution: A mid-ocean ridge-type rift mechanism." Journal of Geophysical Research: Planets 107.E5 (2002).; U.S. Geological Survey, 2002, Controlled photomosaic map of Europa, Je 15M CMN: U.S. Geological Survey Geologic Investigations Series I-2757, available at http
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
Shinde, Pramod; Jalan, Sarika
2015-12-01
Molecular networks act as the backbone of cellular activities, providing an excellent opportunity to understand the developmental changes in an organism. While network data usually constitute only stationary network graphs, constructing a multilayer PPI network may provide clues to the particular developmental role at each stage of life and may unravel the importance of these developmental changes. The developmental biology model of Caenorhabditis elegans analyzed here provides a ripe platform to understand the patterns of evolution during the life stages of an organism. In the present study, the widely studied network properties exhibit overall similar statistics for all the PPI layers. Further, the analysis of the degree-degree correlation and spectral properties not only reveals crucial differences in each PPI layer but also indicates the presence of the varying complexity among them. The PPI layer of the nematode life stage exhibits various network properties different to the rest of the PPI layers, indicating the specific role of cellular diversity and developmental transitions at this stage. The framework presented here provides a direction to explore and understand the developmental changes occurring in the different life stages of an organism.
Triviño, Ana; Congregado, Miguel; Loscertales, Jesús; Cozar, Fernando; Pinos, Nathalie; Carmona, Patricia; Jiménez-Merchán, Rafael; Girón-Arjona, Juan Carlos
2015-01-01
Video-assisted thoracic surgery (VATS) has significantly developed over the last decade. However, a VATS approach for thymoma remains controversial. The aim of this study was to evaluate the feasibility of VATS thymectomy for the treatment of early-stage thymoma and to compare the outcomes with open resection. A comparative study of 59 patients who underwent surgical resection for early stage thymoma (VATS: 44 and open resection: 15) between 1993 and 2011 was performed. Data of patient characteristics, morbidity, mortality, length of hospital stay, the relationship between miasthenia gravis-thymoma, recurrence, and survival were collected for statistical analysis. Thymomas were classified according to Masaoka staging system: 38 in stage I (VATS group: 29 and open group: 9) and 21 in stage II (VATS group: 15 and open group: 6). The mean tumor size in the open group was 7.6cm (13-4cm) and in the VATS group 6.9cm (12-2.5cm). The average length of stay was shorter in the VATS group than in the open group (Pthymoma is technically feasible and is associated with a shorter hospital stay. The 5-year oncologic outcomes were similar in the open and VATS groups. Copyright © 2013 AEC. Publicado por Elsevier España, S.L.U. All rights reserved.
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.
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.
Directory of Open Access Journals (Sweden)
Gavin B Stewart
Full Text Available Individual participant data (IPD meta-analyses that obtain "raw" data from studies rather than summary data typically adopt a "two-stage" approach to analysis whereby IPD within trials generate summary measures, which are combined using standard meta-analytical methods. Recently, a range of "one-stage" approaches which combine all individual participant data in a single meta-analysis have been suggested as providing a more powerful and flexible approach. However, they are more complex to implement and require statistical support. This study uses a dataset to compare "two-stage" and "one-stage" models of varying complexity, to ascertain whether results obtained from the approaches differ in a clinically meaningful way.We included data from 24 randomised controlled trials, evaluating antiplatelet agents, for the prevention of pre-eclampsia in pregnancy. We performed two-stage and one-stage IPD meta-analyses to estimate overall treatment effect and to explore potential treatment interactions whereby particular types of women and their babies might benefit differentially from receiving antiplatelets. Two-stage and one-stage approaches gave similar results, showing a benefit of using anti-platelets (Relative risk 0.90, 95% CI 0.84 to 0.97. Neither approach suggested that any particular type of women benefited more or less from antiplatelets. There were no material differences in results between different types of one-stage model.For these data, two-stage and one-stage approaches to analysis produce similar results. Although one-stage models offer a flexible environment for exploring model structure and are useful where across study patterns relating to types of participant, intervention and outcome mask similar relationships within trials, the additional insights provided by their usage may not outweigh the costs of statistical support for routine application in syntheses of randomised controlled trials. Researchers considering undertaking an IPD
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
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...
Estimation of macro sleep stages from whole night audio analysis.
Dafna, E; Halevi, M; Ben Or, D; Tarasiuk, A; Zigel, Y
2016-08-01
During routine sleep diagnostic procedure, sleep is broadly divided into three states: rapid eye movement (REM), non-REM (NREM) states, and wake, frequently named macro-sleep stages (MSS). In this study, we present a pioneering attempt for MSS detection using full night audio analysis. Our working hypothesis is that there might be differences in sound properties within each MSS due to breathing efforts (or snores) and body movements in bed. In this study, audio signals of 35 patients referred to a sleep laboratory were recorded and analyzed. An additional 178 subjects were used to train a probabilistic time-series model for MSS staging across the night. The audio-based system was validated on 20 out of the 35 subjects. System accuracy for estimating (detecting) epoch-by-epoch wake/REM/NREM states for a given subject is 74% (69% for wake, 54% for REM, and 79% NREM). Mean error (absolute difference) was 36±34 min for detecting total sleep time, 17±21 min for sleep latency, 5±5% for sleep efficiency, and 7±5% for REM percentage. These encouraging results indicate that audio-based analysis can provide a simple and comfortable alternative method for ambulatory evaluation of sleep and its disorders.
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
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.
Higher order statistical frequency domain decomposition for operational modal analysis
Nita, G. M.; Mahgoub, M. A.; Sharyatpanahi, S. G.; Cretu, N. C.; El-Fouly, T. M.
2017-02-01
Experimental methods based on modal analysis under ambient vibrational excitation are often employed to detect structural damages of mechanical systems. Many of such frequency domain methods, such as Basic Frequency Domain (BFD), Frequency Domain Decomposition (FFD), or Enhanced Frequency Domain Decomposition (EFFD), use as first step a Fast Fourier Transform (FFT) estimate of the power spectral density (PSD) associated with the response of the system. In this study it is shown that higher order statistical estimators such as Spectral Kurtosis (SK) and Sample to Model Ratio (SMR) may be successfully employed not only to more reliably discriminate the response of the system against the ambient noise fluctuations, but also to better identify and separate contributions from closely spaced individual modes. It is shown that a SMR-based Maximum Likelihood curve fitting algorithm may improve the accuracy of the spectral shape and location of the individual modes and, when combined with the SK analysis, it provides efficient means to categorize such individual spectral components according to their temporal dynamics as coherent or incoherent system responses to unknown ambient excitations.
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.
Criminal victimization in Ukraine: analysis of statistical data
Directory of Open Access Journals (Sweden)
Serhiy Nezhurbida
2007-12-01
Full Text Available The article is based on the analysis of statistical data provided by law-enforcement, judicial and other bodies of Ukraine. The given analysis allows us to give an accurate quantity of a current status of crime victimization in Ukraine, to characterize its basic features (level, rate, structure, dynamics, and etc.. L’article se concentre sur l’analyse des données statystiques fournies par les institutions de contrôle sociale (forces de police et magistrature et par d’autres organes institutionnels ukrainiens. Les analyses effectuées attirent l'attention sur la situation actuelle des victimes du crime en Ukraine et aident à délinéer leur principales caractéristiques (niveau, taux, structure, dynamiques, etc.L’articolo si basa sull’analisi dei dati statistici forniti dalle agenzie del controllo sociale (forze dell'ordine e magistratura e da altri organi istituzionali ucraini. Le analisi effettuate forniscono molte informazioni sulla situazione attuale delle vittime del crimine in Ucraina e aiutano a delinearne le caratteristiche principali (livello, tasso, struttura, dinamiche, ecc..
A statistical 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.
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
Latest Results From the QuakeFinder Statistical Analysis Framework
Kappler, K. N.; MacLean, L. S.; Schneider, D.; Bleier, T.
2017-12-01
Since 2005 QuakeFinder (QF) has acquired an unique dataset with outstanding spatial and temporal sampling of earth's magnetic field along several active fault systems. This QF network consists of 124 stations in California and 45 stations along fault zones in Greece, Taiwan, Peru, Chile and Indonesia. Each station is equipped with three feedback induction magnetometers, two ion sensors, a 4 Hz geophone, a temperature sensor, and a humidity sensor. Data are continuously recorded at 50 Hz with GPS timing and transmitted daily to the QF data center in California for analysis. QF is attempting to detect and characterize anomalous EM activity occurring ahead of earthquakes. There have been many reports of anomalous variations in the earth's magnetic field preceding earthquakes. Specifically, several authors have drawn attention to apparent anomalous pulsations seen preceding earthquakes. Often studies in long term monitoring of seismic activity are limited by availability of event data. It is particularly difficult to acquire a large dataset for rigorous statistical analyses of the magnetic field near earthquake epicenters because large events are relatively rare. Since QF has acquired hundreds of earthquakes in more than 70 TB of data, we developed an automated approach for finding statistical significance of precursory behavior and developed an algorithm framework. Previously QF reported on the development of an Algorithmic Framework for data processing and hypothesis testing. The particular instance of algorithm we discuss identifies and counts magnetic variations from time series data and ranks each station-day according to the aggregate number of pulses in a time window preceding the day in question. If the hypothesis is true that magnetic field activity increases over some time interval preceding earthquakes, this should reveal itself by the station-days on which earthquakes occur receiving higher ranks than they would if the ranking scheme were random. This can
Statistical analysis of cone penetration resistance of railway ballast
Saussine, Gilles; Dhemaied, Amine; Delforge, Quentin; Benfeddoul, Selim
2017-06-01
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.
STATISTICAL ANALYSIS OF RAW SUGAR MATERIAL FOR SUGAR PRODUCER COMPLEX
Directory of Open Access Journals (Sweden)
A. A. Gromkovskii
2015-01-01
Full Text Available 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 first and second order. It is shown that despite the small amount of experimental data, which provide raw sugar producing enterprises laboratory, using autoregression is justified. The proposed model allows correctly out properly the dynamics of changes raw indexes in the time, which confirms the estimates. In the article highlighted the fact that in the case the predominance trend components in the dynamics of the studied characteristics of sugar beet proposed prediction models provide the better quality of the forecast. In the presence the oscillations portions of the curve describing the change raw performance, for better construction of the forecast required increase number of measurements data. In the article also presents the results of the use adaptive prediction Brown’s model for predicting sugar beet raw performance. The statistical analysis allowed conclusions about the level of quality sufficient to describe changes raw indices for the forecast development. The optimal discount rates data are identified that determined by the form of the curve of growth sugar content of the beet root and mass in the process of maturation. Formulated conclusions of the quality of the forecast, depending on these factors that determines the expert forecaster. In the article shows the calculated expression, derived from experimental data that allow calculate changes of the raw material feature of sugar beet in the process of maturation.
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.
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.
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||.
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
Evaluation of eye irritation potential: statistical analysis and tier testing strategies.
de Silva, O; Cottin, M; Dami, N; Roguet, R; Catroux, P; Toufic, A; Sicard, C; Dossou, K G; Gerner, I; Schlede, E; Spielmann, H; Gupta, K C; Hills, R N
1997-01-01
Eye irritation testing, specifically the Draize test, has been the centre of controversy for many reasons. Several alternatives, based on the principles of reduction, refinement and replacement, have been proposed and are being used by the industry and government authorities. However, no universally applicable, validated non-animal alternative(s) is currently available. This report presents a statistical analysis and two testing approaches: the partial least squares multivariate statistical analysis of de Silva and colleagues from France, the tier-testing approach for regulatory purposes described by Gerner and colleagues from Germany, and the three-step tier-testing approach of the US Interagency Regulatory Alternatives Group described by Gupta and Hill. These approaches were presented as three separate papers at the November 1993 Interagency Regulatory Alternatives Group (IRAG) Workshop on Eye Irritation Testing; they have been summarized and combined into the following three-part report. The first part (de Silva et al.) presents statistical techniques for establishing test batteries of in vitro alternatives to the eye irritation test. The second (Gerner et al.) and third (Gupta and Hill) parts are similar in that they stage assessment of information by using a combination of screening information and animal testing to effect reductions in animal use and distress.
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.
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
3D analysis of spontaneous nystagmus in early stage of vestibular neuritis.
Yagi, T; Koizumi, Yasuo; Sugizaki, Kazuki
2010-04-01
The pathological localization of vestibular neuritis is still controversial. Analyses of the spontaneous nystagmus support the temporal bone studies, which indicated the location of the pathology to be in the superior vestibular nerve. However, based on the data from the head impulse testing the pathology is in the vestibular nerve including the inferior branch. Twenty-three patients with vestibular neuritis participated in this study. The spontaneous nystagmus was recorded within 1 week after the onset of the disease. Three-dimensional analysis of the nystagmus was performed using video image analysis system. The rotation axis was calculated and compared to the anatomical axes of the semicircular canals. The axes of the spontaneous nystagmus in all patients were scattered around the axes of horizontal and anterior canals, especially between the compound axis of anterior and horizontal canals and the axis of horizontal canal. The statistical analysis revealed that in the quite early stage of the disease (day 0-2 of the attack), the spontaneous nystagmus tended to have more torsional eye movements as compared to the less early stage (day 3-6). The present study strongly suggests that the pathology of vestibular neuritis is in the superior vestibular nerve branch. Also it can be speculated that at the early stage of this disease, the pathology is in the whole branch of the nerve. Subsequently, the anterior canal branch recovers faster than the horizontal canal branch. Copyright (c) 2009 Elsevier Ireland Ltd. All rights reserved.
Statistical analysis of CSP plants by simulating extensive meteorological series
Pavón, Manuel; Fernández, Carlos M.; Silva, Manuel; Moreno, Sara; Guisado, María V.; Bernardos, Ana
2017-06-01
The feasibility analysis of any power plant project needs the estimation of the amount of energy it will be able to deliver to the grid during its lifetime. To achieve this, its feasibility study requires a precise knowledge of the solar resource over a long term period. In Concentrating Solar Power projects (CSP), financing institutions typically requires several statistical probability of exceedance scenarios of the expected electric energy output. Currently, the industry assumes a correlation between probabilities of exceedance of annual Direct Normal Irradiance (DNI) and energy yield. In this work, this assumption is tested by the simulation of the energy yield of CSP plants using as input a 34-year series of measured meteorological parameters and solar irradiance. The results of this work show that, even if some correspondence between the probabilities of exceedance of annual DNI values and energy yields is found, the intra-annual distribution of DNI may significantly affect this correlation. This result highlights the need of standardized procedures for the elaboration of representative DNI time series representative of a given probability of exceedance of annual DNI.
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.
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.
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.
Statistical analysis and optimization of igbt manufacturing flow
Directory of Open Access Journals (Sweden)
Baranov V. V.
2015-02-01
Full Text Available The use of computer simulation, design and optimization of power electronic devices formation technological processes can significantly reduce development time, improve the accuracy of calculations, choose the best options for implementation based on strict mathematical analysis. One of the most common power electronic devices is isolated gate bipolar transistor (IGBT, which combines the advantages of MOSFET and bipolar transistor. The achievement of high requirements for these devices is only possible by optimizing device design and manufacturing process parameters. Therefore important and necessary step in the modern cycle of IC design and manufacturing is to carry out the statistical analysis. Procedure of the IGBT threshold voltage optimization was realized. Through screening experiments according to the Plackett-Burman design the most important input parameters (factors that have the greatest impact on the output characteristic was detected. The coefficients of the approximation polynomial adequately describing the relationship between the input parameters and investigated output characteristics ware determined. Using the calculated approximation polynomial, a series of multiple, in a cycle of Monte Carlo, calculations to determine the spread of threshold voltage values at selected ranges of input parameters deviation were carried out. Combinations of input process parameters values were determined randomly by a normal distribution within a given range of changes. The procedure of IGBT process parameters optimization consist a mathematical problem of determining the value range of the input significant structural and technological parameters providing the change of the IGBT threshold voltage in a given interval. The presented results demonstrate the effectiveness of the proposed optimization techniques.
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.
Allen, Kirk
The Statistics Concept Inventory (SCI) is a multiple choice test designed to assess students' conceptual understanding of topics typically encountered in an introductory statistics course. This dissertation documents the development of the SCI from Fall 2002 up to Spring 2006. The first phase of the project essentially sought to answer the question: "Can you write a test to assess topics typically encountered in introductory statistics?" Book One presents the results utilized in answering this question in the affirmative. The bulk of the results present the development and evolution of the items, primarily relying on objective metrics to gauge effectiveness but also incorporating student feedback. The second phase boils down to: "Now that you have the test, what else can you do with it?" This includes an exploration of Cronbach's alpha, the most commonly-used measure of test reliability in the literature. An online version of the SCI was designed, and its equivalency to the paper version is assessed. Adding an extra wrinkle to the online SCI, subjects rated their answer confidence. These results show a general positive trend between confidence and correct responses. However, some items buck this trend, revealing potential sources of misunderstandings, with comparisons offered to the extant statistics and probability educational research. The third phase is a re-assessment of the SCI: "Are you sure?" A factor analytic study favored a uni-dimensional structure for the SCI, although maintaining the likelihood of a deeper structure if more items can be written to tap similar topics. A shortened version of the instrument is proposed, demonstrated to be able to maintain a reliability nearly identical to that of the full instrument. Incorporating student feedback and a faculty topics survey, improvements to the items and recommendations for further research are proposed. The state of the concept inventory movement is assessed, to offer a comparison to the work presented
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.
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
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.
Zhang, Fan; Wu, Weining; Ning, Lipeng; McAnulty, Gloria; Waber, Deborah; Gagoski, Borjan; Sarill, Kiera; Hamoda, Hesham M; Song, Yang; Cai, Weidong; Rathi, Yogesh; O'Donnell, Lauren J
2018-05-01
This work presents a suprathreshold fiber cluster (STFC) method that leverages the whole brain fiber geometry to enhance statistical group difference analyses. The proposed method consists of 1) a well-established study-specific data-driven tractography parcellation to obtain white matter tract parcels and 2) a newly proposed nonparametric, permutation-test-based STFC method to identify significant differences between study populations. The basic idea of our method is that a white matter parcel's neighborhood (nearby parcels with similar white matter anatomy) can support the parcel's statistical significance when correcting for multiple comparisons. We propose an adaptive parcel neighborhood strategy to allow suprathreshold fiber cluster formation that is robust to anatomically varying inter-parcel distances. The method is demonstrated by application to a multi-shell diffusion MRI dataset from 59 individuals, including 30 attention deficit hyperactivity disorder patients and 29 healthy controls. Evaluations are conducted using both synthetic and in-vivo data. The results indicate that the STFC method gives greater sensitivity in finding group differences in white matter tract parcels compared to several traditional multiple comparison correction methods. Copyright © 2018 Elsevier Inc. All rights reserved.
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.
Statistical analysis of compressive low rank tomography with random measurements
Acharya, Anirudh; Guţă, Mădălin
2017-05-01
We consider the statistical problem of ‘compressive’ estimation of low rank states (r\\ll d ) with random basis measurements, where r, d are the rank and dimension of the state respectively. We investigate whether for a fixed sample size N, the estimation error associated with a ‘compressive’ measurement setup is ‘close’ to that of the setting where a large number of bases are measured. We generalise and extend previous results, and show that the mean square error (MSE) associated with the Frobenius norm attains the optimal rate rd/N with only O(r log{d}) random basis measurements for all states. An important tool in the analysis is the concentration of the Fisher information matrix (FIM). We demonstrate that although a concentration of the MSE follows from a concentration of the FIM for most states, the FIM fails to concentrate for states with eigenvalues close to zero. We analyse this phenomenon in the case of a single qubit and demonstrate a concentration of the MSE about its optimal despite a lack of concentration of the FIM for states close to the boundary of the Bloch sphere. We also consider the estimation error in terms of a different metric-the quantum infidelity. We show that a concentration in the mean infidelity (MINF) does not exist uniformly over all states, highlighting the importance of loss function choice. Specifically, we show that for states that are nearly pure, the MINF scales as 1/\\sqrt{N} but the constant converges to zero as the number of settings is increased. This demonstrates a lack of ‘compressive’ recovery for nearly pure states in this metric.
SUBMILLIMETER NUMBER COUNTS FROM STATISTICAL ANALYSIS OF BLAST MAPS
International Nuclear Information System (INIS)
Patanchon, Guillaume; Ade, Peter A. R.; Griffin, Matthew; Hargrave, Peter C.; Mauskopf, Philip; Moncelsi, Lorenzo; Pascale, Enzo; Bock, James J.; Chapin, Edward L.; Halpern, Mark; Marsden, Gaelen; Scott, Douglas; Devlin, Mark J.; Dicker, Simon R.; Klein, Jeff; Rex, Marie; Gundersen, Joshua O.; Hughes, David H.; Netterfield, Calvin B.; Olmi, Luca
2009-01-01
We describe the application of a statistical method to estimate submillimeter galaxy number counts from confusion-limited observations by the Balloon-borne Large Aperture Submillimeter Telescope (BLAST). Our method is based on a maximum likelihood fit to the pixel histogram, sometimes called 'P(D)', an approach which has been used before to probe faint counts, the difference being that here we advocate its use even for sources with relatively high signal-to-noise ratios. This method has an advantage over standard techniques of source extraction in providing an unbiased estimate of the counts from the bright end down to flux densities well below the confusion limit. We specifically analyze BLAST observations of a roughly 10 deg 2 map centered on the Great Observatories Origins Deep Survey South field. We provide estimates of number counts at the three BLAST wavelengths 250, 350, and 500 μm; instead of counting sources in flux bins we estimate the counts at several flux density nodes connected with power laws. We observe a generally very steep slope for the counts of about -3.7 at 250 μm, and -4.5 at 350 and 500 μm, over the range ∼0.02-0.5 Jy, breaking to a shallower slope below about 0.015 Jy at all three wavelengths. We also describe how to estimate the uncertainties and correlations in this method so that the results can be used for model-fitting. This method should be well suited for analysis of data from the Herschel satellite.
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
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
Directory of Open Access Journals (Sweden)
Kathy Ahern
2002-09-01
Full Text Available This study investigates triangulation of the findings of a qualitative analysis by applying an exploratory factor analysis to themes identified in a phenomenological study. A questionnaire was developed from a phenomenological analysis of parents' experiences of parenting a child with Developmental Coordination Disorder (DCD. The questionnaire was administered to 114 parents of DCD children and data were analyzed using an exploratory factor analysis. The extracted factors provided support for the validity of the original qualitative analysis, and a commentary on the validity of the process is provided. The emerging description is of the compromises that were necessary to translate qualitative themes into statistical factors, and of the ways in which the statistical analysis suggests further qualitative study.
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
Climate time series analysis classical statistical and bootstrap methods
Mudelsee, Manfred
2010-01-01
This book presents bootstrap resampling as a computationally intensive method able to meet the challenges posed by the complexities of analysing climate data. It shows how the bootstrap performs reliably in the most important statistical estimation techniques.
A Statistical Analysis of the Nuffield Physical Science Project Assessment
Hockey, S. W.
1973-01-01
Discusses measurement techniques developed in the Nuffield A level physical science assessment and statistical results obtained in 1968 and 1971. Concludes that individual projects are contributors of positive and valuable educational experiences to the course. (CC)
statistical analysis of wind speed for electrical power generation
African Journals Online (AJOL)
HOD
1, 4, 5 DEPARTMENT OF ELECTRICAL AND ELECTRONICS ENGINEERING, UNIVERSITY OF ILORIN, KWARA STATE, NIGERIA. 2DEPARTMENT OF ... Keywords: Wind speed - probability - density function – wind energy conversion system- statistical analyses. 1. ..... weather data for energy assessments of hybrid.
Statistical Methods for Analysis of Neurofibromatosis Clinical Data
National Research Council Canada - National Science Library
Joe, Harry
2002-01-01
... to the burden of the disease. The goals of this project are to devise new statistical methods to find patterns and relationships within the phenotypes and genotypes of people with NF, and to effectively model tumor formation in these disorders...
Petocz, Agnes; Newbery, Glenn
2010-01-01
Statistics education in psychology often falls disappointingly short of its goals. The increasing use of qualitative approaches in statistics education research has extended and enriched our understanding of statistical cognition processes, and thus facilitated improvements in statistical education and practices. Yet conceptual analysis, a…
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.
Directory of Open Access Journals (Sweden)
Ceena Denny
2009-01-01
Full Text Available Objective : The aim of the study was to assess the severity of the disease in oral submucous fibrosis (OSF, correlate the clinical, functional staging with histopathological staging, and analyze collagen distribution in different stages of OSF using the picrosirius red stain under polarizing microscopy. Materials and Methods : The study included randomly incorporated 50 subjects, of whom 40 were patients with OSF, and 10 were in the control group. Clinical, functional staging in OSF cases was done depending upon definite criteria. A histopathological study was conducted using the hematoxylin and eosin stain and picrosirius red stain. Collagen fibers were analyzed for thickness and polarizing colors. Furthermore, clinical, functional, and histopathological stages were compared. Statistical Analysis : Descriptive data which included mean, SD, and percentages were calculated for each group. Categorical data were analyzed by the chi-square test. Multiple group comparisons were made by one-way ANOVA followed by Student′s t-test for pairwise comparisons. For all tests, a P-value of 0.05 or less was considered for statistical significance. Results : As the severity of the disease increased, clinically, there was definite progression in subjective and objective symptoms. Polarized microscopic, examination revealed, there was a gradual decrease in the green-greenish yellow color of the fibers and a shift to orange red-red color with increase in severity of the disease. Thereby, it appeared that the tight packing of collagen fibers in OSF progressively increased as the disease progressed from early to advanced stages. We observed that the comparison of functional staging with histopathological staging was a more reliable indicator of the severity of the disease. Conclusion : In the present study, we observed that mouth opening was restricted with advancing stages of OSF. The investigation also points to the importance of assessing the cases of OSF
SPECT image analysis using statistical parametric mapping in patients with Parkinson's disease.
Imon, Y; Matsuda, H; Ogawa, M; Kogure, D; Sunohara, N
1999-10-01
This study investigated alterations in regional cerebral blood flow (rCBF) in patients with Parkinson's disease using statistical parametric mapping (SPM). Noninvasive rCBF measurements using 99mTc-ethyl cysteinate dimer (ECD) SPECT were performed on 28 patients with Parkinson's disease and 48 age-matched healthy volunteers. The Parkinson's disease patients were divided into two groups, 16 patients with Hoehn and Yahr stage I or II and 12 patients with Hoehn and Yahr stage III or IV. We used the raw data (absolute rCBF parametric maps) and the adjusted rCBF images in relative flow distribution (normalization of global CBF for each subject to 50 mL/100 g/min with proportional scaling) to compare these groups with SPM. In patients with stage I or II Parkinson's disease, we found a diffuse decrease in absolute rCBF in the whole brain with sparing of the central gray matter, hippocampus and right lower temporal lobe compared with healthy volunteers. Adjusted rCBF increased in both putamina and the right hippocampus. In patients with stage III or IV disease, rCBF decreased throughout the whole brain. Adjusted rCBF increased bilaterally in the putamina, globi pallidi, hippocampi and cerebellar hemispheres (dentate nuclei) and in the left ventrolateral thalamus, right insula and right inferior temporal gyrus. SPM analysis showed that significant rCBF changes in Parkinson's disease accompanied disease progression and related to disease pathophysiology in the functional architecture of thalamocortex-basal ganglia circuits and related systems.
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...
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.
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.
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 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...
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
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
Multivariate Analysis and Statistics in Pharmaceutical Process Research and Development.
Tabora, José E; Domagalski, Nathan
2017-06-07
The application of statistics in pharmaceutical process research and development has evolved significantly over the past decades, motivated in part by the introduction of the Quality by Design paradigm, a landmark change in regulatory expectations for the level of scientific understanding associated with the manufacturing process. Today, statistical methods are increasingly applied to accelerate the characterization and optimization of new drugs created via numerous unit operations well known to the chemical engineering discipline. We offer here a review of the maturity in the implementation of design of experiment techniques, the increased incorporation of latent variable methods in process and material characterization, and the adoption of Bayesian methodology for process risk assessment.
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
A Bayesian Statistical Analysis of the Enhanced Greenhouse Effect
de Vos, A.F.; Tol, R.S.J.
1998-01-01
This paper demonstrates that there is a robust statistical relationship between the records of the global mean surface air temperature and the atmospheric concentration of carbon dioxide over the period 1870-1991. As such, the enhanced greenhouse effect is a plausible explanation for the observed
Statistical analysis of the profile of consumer Internet services
Arzhenovskii Sergei Valentinovich; Sountoura Lansine
2014-01-01
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 Lineament Analysis in South Greenland Based on Landsat Imagery
DEFF Research Database (Denmark)
Conradsen, Knut; Nilsson, Gert; Thyrsted, Tage
1986-01-01
Linear features, mapped visually from MSS channel-7 photoprints (1: 1 000 000) of Landsat images from South Greenland, were digitized and analyzed statistically. A sinusoidal curve was fitted to the frequency distribution which was then divided into ten significant classes of azimuthal trends. Maps...
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 ...
Statistical Analysis of Large-Scale Structure of Universe
Tugay, A. V.
While galaxy cluster catalogs were compiled many decades ago, other structural elements of cosmic web are detected at definite level only in the newest works. For example, extragalactic filaments were described by velocity field and SDSS galaxy distribution during the last years. Large-scale structure of the Universe could be also mapped in the future using ATHENA observations in X-rays and SKA in radio band. Until detailed observations are not available for the most volume of Universe, some integral statistical parameters can be used for its description. Such methods as galaxy correlation function, power spectrum, statistical moments and peak statistics are commonly used with this aim. The parameters of power spectrum and other statistics are important for constraining the models of dark matter, dark energy, inflation and brane cosmology. In the present work we describe the growth of large-scale density fluctuations in one- and three-dimensional case with Fourier harmonics of hydrodynamical parameters. In result we get power-law relation for the matter power spectrum.
Herbal gardens of India: A statistical analysis report | Rao | African ...
African Journals Online (AJOL)
A knowledge system of the herbal garden in India was developed and these herbal gardens' information was statistically classified for efficient data processing, sharing and retrieving of information, which could act as a decision tool to the farmers, researchers, decision makers and policy makers in the field of medicinal ...
On cumulative process model and its statistical analysis
Czech Academy of Sciences Publication Activity Database
Volf, Petr
2000-01-01
Roč. 36, č. 2 (2000), s. 165-176 ISSN 0023-5954 R&D Projects: GA ČR GA201/97/0354; GA ČR GA402/98/0742 Institutional research plan: AV0Z1075907 Subject RIV: BB - Applied Statistics, Operational Research
Did Tanzania Achieve the Second Millennium Development Goal? Statistical Analysis
Magoti, Edwin
2016-01-01
Development Goal "Achieve universal primary education", the challenges faced, along with the way forward towards achieving the fourth Sustainable Development Goal "Ensure inclusive and equitable quality education and promote lifelong learning opportunities for all". Statistics show that Tanzania has made very promising steps…
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....... This approach will show how the process develops from a data point of view. The procedure is illustrated on a relatively simple industrial batch process, but it is also applicable in a general context, where knowledge about the variables is available....... 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...
EventThread: Visual Summarization and Stage Analysis of Event Sequence Data.
Guo, Shunan; Xu, Ke; Zhao, Rongwen; Gotz, David; Zha, Hongyuan; Cao, Nan
2018-01-01
Event sequence data such as electronic health records, a person's academic records, or car service records, are ordered series of events which have occurred over a period of time. Analyzing collections of event sequences can reveal common or semantically important sequential patterns. For example, event sequence analysis might reveal frequently used care plans for treating a disease, typical publishing patterns of professors, and the patterns of service that result in a well-maintained car. It is challenging, however, to visually explore large numbers of event sequences, or sequences with large numbers of event types. Existing methods focus on extracting explicitly matching patterns of events using statistical analysis to create stages of event progression over time. However, these methods fail to capture latent clusters of similar but not identical evolutions of event sequences. In this paper, we introduce a novel visualization system named EventThread which clusters event sequences into threads based on tensor analysis and visualizes the latent stage categories and evolution patterns by interactively grouping the threads by similarity into time-specific clusters. We demonstrate the effectiveness of EventThread through usage scenarios in three different application domains and via interviews with an expert user.
Statistical methods for data analysis in particle physics
Lista, Luca
2017-01-01
This concise set of course-based notes provides the reader with the main concepts and tools needed to perform statistical analyses of experimental data, in particular in the field of high-energy physics (HEP). First, the book provides an introduction to probability theory and basic statistics, mainly intended as a refresher from readers’ advanced undergraduate studies, but also to help them clearly distinguish between the Frequentist and Bayesian approaches and interpretations in subsequent applications. More advanced concepts and applications are gradually introduced, culminating in the chapter on both discoveries and upper limits, as many applications in HEP concern hypothesis testing, where the main goal is often to provide better and better limits so as to eventually be able to distinguish between competing hypotheses, or to rule out some of them altogether. Many worked-out examples will help newcomers to the field and graduate students alike understand the pitfalls involved in applying theoretical co...
STATISTICAL ANALYSYS OF THE SCFE OF A BRAZILAN MINERAL COAL
Directory of Open Access Journals (Sweden)
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.
Integration of Advanced Statistical Analysis Tools and Geophysical Modeling
2012-08-01
1.56 0.48 Beale: MetalMapper Cued: Beale_MMstat Target: 477 Cell 202 of 1547 (SOI, 2OI) Model 1 of 3 (Inv #1 / 2 = SOI: 1 / 1) Tag...Statistical classification of buried unexploded ordnance using nonparametric prior models. IEEE Trans. Geosci. Remote Sensing, 45: 2794–2806, 2007. T...Bell and B. Barrow. Subsurface discrimination using electromagnetic induction sensors. IEEE Trans. Geosci. Remote Sensing, 39:1286–1293, 2001. S. D
Advocacy, analysis and quality. The Bermuda triangle of Statistics
SAISANA Michaela
2013-01-01
One might muse that what official statistics are to the consolidation of the modern nation state, composite indicators are to the emergence of post-modernity, – meaning by this the philosophical critique of the exact science and rational knowledge programme of Descartes and Galileo. Composite indicators give voice to a plurality of different actors and normative views of post-modernity. Not only has the use of composite indicators increased dramatically over the past ten to fifteen years, ...
Detailed statistical analysis plan for the pulmonary protection trial
DEFF Research Database (Denmark)
Buggeskov, Katrine B; Jakobsen, Janus C; Secher, Niels H
2014-01-01
BACKGROUND: Pulmonary dysfunction complicates cardiac surgery that includes cardiopulmonary bypass. The pulmonary protection trial evaluates effect of pulmonary perfusion on pulmonary function in patients suffering from chronic obstructive pulmonary disease. This paper presents the statistical plan...... serious adverse events: pneumothorax or pleural effusion requiring drainage, major bleeding, reoperation, severe infection, cerebral event, hyperkaliemia, acute myocardial infarction, cardiac arrhythmia, renal replacement therapy, and readmission for a respiratory-related problem. CONCLUSIONS...
Learning to Translate: A Statistical and Computational Analysis
Directory of Open Access Journals (Sweden)
Marco Turchi
2012-01-01
Full Text Available We present an extensive experimental study of Phrase-based Statistical Machine Translation, from the point of view of its learning capabilities. Very accurate Learning Curves are obtained, using high-performance computing, and extrapolations of the projected performance of the system under different conditions are provided. Our experiments confirm existing and mostly unpublished beliefs about the learning capabilities of statistical machine translation systems. We also provide insight into the way statistical machine translation learns from data, including the respective influence of translation and language models, the impact of phrase length on performance, and various unlearning and perturbation analyses. Our results support and illustrate the fact that performance improves by a constant amount for each doubling of the data, across different language pairs, and different systems. This fundamental limitation seems to be a direct consequence of Zipf law governing textual data. Although the rate of improvement may depend on both the data and the estimation method, it is unlikely that the general shape of the learning curve will change without major changes in the modeling and inference phases. Possible research directions that address this issue include the integration of linguistic rules or the development of active learning procedures.
Performance Analysis of Statistical Time Division Multiplexing Systems
Directory of Open Access Journals (Sweden)
Johnson A. AJIBOYE
2010-12-01
Full Text Available Multiplexing is a way of accommodating many input sources of a low capacity over a high capacity outgoing channel. Statistical Time Division Multiplexing (STDM is a technique that allows the number of users to be multiplexed over the channel more than the channel can afford. The STDM normally exploits unused time slots by the non-active users and allocates those slots for the active users. Therefore, STDM is appropriate for bursty sources. In this way STDM normally utilizes channel bandwidth better than traditional Time Division Multiplexing (TDM. In this work, the statistical multiplexer is viewed as M/M/1queuing system and the performance is measured by comparing analytical results to simulation results using Matlab. The index used to determine the performance of the statistical multiplexer is the number of packets both in the system and the queue. Comparison of analytical results was also done between M/M/1 and M/M/2 and also between M/M/1 and M/D/1 queue systems. At high utilizations, M/M/2 performs better than M/M/1. M/D/1 also outperforms M/M1.
The Digital Divide in Romania – A Statistical Analysis
Directory of Open Access Journals (Sweden)
Daniela BORISOV
2012-06-01
Full Text Available The digital divide is a subject of major importance in the current economic circumstances in which Information and Communication Technologies (ICT are seen as a significant determinant of increasing the domestic competitiveness and contribute to better life quality. Latest international reports regarding various aspects of ICT usage in modern society reveal a decrease of overall digital disparity towards the average trends of the worldwide ITC’s sector – this relates to latest advances of mobile and computer penetration rates, both for personal use and for households/ business. In Romania, the low starting point in the development of economy and society in the ICT direction was, in some extent, compensated by the rapid annual growth of the last decade. Even with these dynamic developments, the statistical data still indicate poor positions in European Union hierarchy; in this respect, the prospects of a rapid recovery of the low performance of the Romanian ICT endowment and usage and the issue continue to be regarded as a challenge for progress in economic and societal terms. The paper presents several methods for assessing the current state of ICT related aspects in terms of Internet usage based on the latest data provided by international databases. The current position of Romanian economy is judged according to several economy using statistical methods based on variability measurements: the descriptive statistics indicators, static measures of disparities and distance metrics.
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...
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.
Post-processing for statistical image analysis in light microscopy.
Cardullo, Richard A; Hinchcliffe, Edward H
2013-01-01
Image processing of images serves a number of important functions including noise reduction, contrast enhancement, and feature extraction. Whatever the final goal, an understanding of the nature of image acquisition and digitization and subsequent mathematical manipulations of that digitized image is essential. Here we discuss the basic mathematical and statistical processes that are routinely used by microscopists to routinely produce high quality digital images and to extract key features of interest using a variety of extraction and thresholding tools. Copyright © 2013 Elsevier Inc. All rights reserved.
Statistical analysis of DNT detection using chemically functionalized microcantilever arrays
DEFF Research Database (Denmark)
Bosco, Filippo; Bache, M.; Hwu, E.-T.
2012-01-01
from 1 to 2 cantilevers have been reported, without any information on repeatability and reliability of the presented data. In explosive detection high reliability is needed and thus a statistical measurement approach needs to be developed and implemented. We have developed a DVD-based read-out system...... capable of generating large sets of cantilever data for vapor and liquid phase detection of 2,4-dinitrotoluene (DNT). Gold coated cantilevers are initially functionalized with tetraTTF-calix[4]pyrrole molecules, specifically designed to bind nitro-aromatic compounds. The selective binding of DNT molecules...
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
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.
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...... is available about the soil parameter distribution.The present paper shows how a characteristic value by computer calcula-tions can be assessed systematically from the actual sample of censored datasupplemented with prior information from a soil parameter data base....
Statistical analysis of phase formation in 2D colloidal systems.
Carstensen, Hauke; Kapaklis, Vassilios; Wolff, Max
2018-01-23
Colloidal systems offer unique opportunities for the study of phase formation and structure since their characteristic length scales are accessible to visible light. As a model system the two-dimensional assembly of colloidal magnetic and non-magnetic particles dispersed in a ferrofluid (FF) matrix is studied by transmission optical microscopy. We present a method to statistically evaluate images with thousands of particles and map phases by extraction of local variables. Different lattice structures and long-range connected branching chains are observed, when tuning the effective magnetic interaction and varying particle ratios.
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.
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)
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.
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.
EFFICIENCY OF KNOWLEDGE TRANSFER THROUGH KNOWLEDGE TEXTS: STATISTICAL ANALYSIS
Directory of Open Access Journals (Sweden)
RAUCHOVÁ, Tereza
2013-03-01
Full Text Available Texts are an important way to share and transfer knowledge. In this paper we analyse the impact of a specific form of texts, so called “knowledge texts”, on the efficiency of knowledge transfer. The objective is to verify or reject several hypotheses on the relationships among the style of educational texts (standard or knowledge styles, learning outcomes (performance of the students after learning and subjective evaluation of conformity of working with individual styles of the texts. For this purpose, we carry out experiment with a homogeneous group of the students (n = 41 divided into an experimental group and a control group. We use statistical methods to process the results of the experiments; ability of the students to solve specific tasks and their opinions on readability and understandability of the texts subject to the time spent for learning. Even if we determine statistically significant relationships between the style of texts and accuracy of the problem solving in the experimental group only, the results allow us to improve the experiment and apply the methodology developed in a less structured branch than the Operational Research (Graph Theory is. The methodology is another benefit of the paper, because it can be applied independently on a particular domain.
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...
Laird, Heather; Vande Kemp, Hendrika
1987-01-01
Explored the level of family therapist complementarity in the early, middle and late stages of therapy performing a micro-analysis of Salvador Minuchin with one family in successful therapy. Level of therapist complementarity was signficantly greater in the early and late stages than in the middle stage, and was significantly correlated with…
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
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)
Stage efficiency in the analysis of thermochemical water decomposition processes
Conger, W. L.; Funk, J. E.; Carty, R. H.; Soliman, M. A.; Cox, K. E.
1976-01-01
The procedure for analyzing thermochemical water-splitting processes using the figure of merit is expanded to include individual stage efficiencies and loss coefficients. The use of these quantities to establish the thermodynamic insufficiencies of each stage is shown. A number of processes are used to illustrate these concepts and procedures and to demonstrate the facility with which process steps contributing most to the cycle efficiency are found. The procedure allows attention to be directed to those steps of the process where the greatest increase in total cycle efficiency can be obtained.
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
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 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 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 Haralick Texture Features to Discriminate Lung Abnormalities
Zayed, Nourhan; Elnemr, Heba A.
2015-01-01
The Haralick texture features are a well-known mathematical method to detect the lung abnormalities and give the opportunity to the physician to localize the abnormality tissue type, either lung tumor or pulmonary edema. In this paper, statistical evaluation of the different features will represent the reported performance of the proposed method. Thirty-seven patients CT datasets with either lung tumor or pulmonary edema were included in this study. The CT images are first preprocessed for noise reduction and image enhancement, followed by segmentation techniques to segment the lungs, and finally Haralick texture features to detect the type of the abnormality within the lungs. In spite of the presence of low contrast and high noise in images, the proposed algorithms introduce promising results in detecting the abnormality of lungs in most of the patients in comparison with the normal and suggest that some of the features are significantly recommended than others. PMID:26557845
Statistical Analysis of Haralick Texture Features to Discriminate Lung Abnormalities
Directory of Open Access Journals (Sweden)
Nourhan Zayed
2015-01-01
Full Text Available The Haralick texture features are a well-known mathematical method to detect the lung abnormalities and give the opportunity to the physician to localize the abnormality tissue type, either lung tumor or pulmonary edema. In this paper, statistical evaluation of the different features will represent the reported performance of the proposed method. Thirty-seven patients CT datasets with either lung tumor or pulmonary edema were included in this study. The CT images are first preprocessed for noise reduction and image enhancement, followed by segmentation techniques to segment the lungs, and finally Haralick texture features to detect the type of the abnormality within the lungs. In spite of the presence of low contrast and high noise in images, the proposed algorithms introduce promising results in detecting the abnormality of lungs in most of the patients in comparison with the normal and suggest that some of the features are significantly recommended than others.
Statistical analysis of intramembranous particles using freeze fracture specimens.
Schladitz, Katja; Särkkä, Aila; Pavenstädt, Iris; Haferkamp, Otto; Mattfeldt, Torsten
2003-08-01
We studied the point processes of intramembranous particles of mitochondrial membranes from HeLa cells using the freeze fracture technique. Three groups - under normal conditions, after exposition with rotenone, and after exposition with sodium acid - were compared. First, we used several summary statistics in order to study the two-dimensional point patterns of intramembranous particles within each group. Then, we compared the patterns in different groups by bootstrap tests using the K-function and the nearest neighbour distance function G(r). Estimation of the G-function provided significant results but no significant differences between groups were found using the classical K-function; estimation of G(r) should therefore not be omitted when studying observed planar point patterns.
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)
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...
Consolidity analysis for fully fuzzy functions, matrices, probability and statistics
Walaa Ibrahim Gabr
2015-01-01
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, ...
[Statistical analysis of German radiologic periodicals: developmental trends in the last 10 years].
Golder, W
1999-09-01
To identify which statistical tests are applied in German radiological publications, to what extent their use has changed during the last decade, and which factors might be responsible for this development. The major articles published in "ROFO" and "DER RADIOLOGE" during 1988, 1993 and 1998 were reviewed for statistical content. The contributions were classified by principal focus and radiological subspecialty. The methods used were assigned to descriptive, basal and advanced statistics. Sample size, significance level and power were established. The use of experts' assistance was monitored. Finally, we calculated the so-called cumulative accessibility of the publications. 525 contributions were found to be eligible. In 1988, 87% used descriptive statistics only, 12.5% basal, and 0.5% advanced statistics. The corresponding figures in 1993 and 1998 are 62 and 49%, 32 and 41%, and 6 and 10%, respectively. Statistical techniques were most likely to be used in research on musculoskeletal imaging and articles dedicated to MRI. Six basic categories of statistical methods account for the complete statistical analysis appearing in 90% of the articles. ROC analysis is the single most common advanced technique. Authors make increasingly use of statistical experts' opinion and programs. During the last decade, the use of statistical methods in German radiological journals has fundamentally improved, both quantitatively and qualitatively. Presently, advanced techniques account for 20% of the pertinent statistical tests. This development seems to be promoted by the increasing availability of statistical analysis software.
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.
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)
New Statistical Approach to the Analysis of Hierarchical Data
Neuman, S. P.; Guadagnini, A.; Riva, M.
2014-12-01
Many variables possess a hierarchical structure reflected in how their increments vary in space and/or time. Quite commonly the increments (a) fluctuate in a highly irregular manner; (b) possess symmetric, non-Gaussian frequency distributions characterized by heavy tails that often decay with separation distance or lag; (c) exhibit nonlinear power-law scaling of sample structure functions in a midrange of lags, with breakdown in such scaling at small and large lags; (d) show extended power-law scaling (ESS) at all lags; and (e) display nonlinear scaling of power-law exponent with order of sample structure function. Some interpret this to imply that the variables are multifractal, which explains neither breakdowns in power-law scaling nor ESS. We offer an alternative interpretation consistent with all above phenomena. It views data as samples from stationary, anisotropic sub-Gaussian random fields subordinated to truncated fractional Brownian motion (tfBm) or truncated fractional Gaussian noise (tfGn). The fields are scaled Gaussian mixtures with random variances. Truncation of fBm and fGn entails filtering out components below data measurement or resolution scale and above domain scale. Our novel interpretation of the data allows us to obtain maximum likelihood estimates of all parameters characterizing the underlying truncated sub-Gaussian fields. These parameters in turn make it possible to downscale or upscale all statistical moments to situations entailing smaller or larger measurement or resolution and sampling scales, respectively. They also allow one to perform conditional or unconditional Monte Carlo simulations of random field realizations corresponding to these scales. Aspects of our approach are illustrated on field and laboratory measured porous and fractured rock permeabilities, as well as soil texture characteristics and neural network estimates of unsaturated hydraulic parameters in a deep vadose zone near Phoenix, Arizona. We also use our approach
Testing normality using the summary statistics with application to meta-analysis
Luo, Dehui; Wan, Xiang; Liu, Jiming; Tong, Tiejun
2018-01-01
As the most important tool to provide high-level evidence-based medicine, researchers can statistically summarize and combine data from multiple studies by conducting meta-analysis. In meta-analysis, mean differences are frequently used effect size measurements to deal with continuous data, such as the Cohen's d statistic and Hedges' g statistic values. To calculate the mean difference based effect sizes, the sample mean and standard deviation are two essential summary measures. However, many...
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)
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 language analysis for automatic exfiltration event detection.
Energy Technology Data Exchange (ETDEWEB)
Robinson, David Gerald
2010-04-01
This paper discusses the recent development a statistical approach for the automatic identification of anomalous network activity that is characteristic of exfiltration events. This approach is based on the language processing method eferred to as latent dirichlet allocation (LDA). Cyber security experts currently depend heavily on a rule-based framework for initial detection of suspect network events. The application of the rule set typically results in an extensive list of uspect network events that are then further explored manually for suspicious activity. The ability to identify anomalous network events is heavily dependent on the experience of the security personnel wading through the network log. Limitations f this approach are clear: rule-based systems only apply to exfiltration behavior that has previously been observed, and experienced cyber security personnel are rare commodities. Since the new methodology is not a discrete rule-based pproach, it is more difficult for an insider to disguise the exfiltration events. A further benefit is that the methodology provides a risk-based approach that can be implemented in a continuous, dynamic or evolutionary fashion. This permits uspect network activity to be identified early with a quantifiable risk associated with decision making when responding to suspicious activity.
AN ANALYSIS OF SOME RECENT STATISTICS OF THE ROMANIAN TOURISM
Directory of Open Access Journals (Sweden)
Iuliana BUCURESCU
2011-06-01
Full Text Available One studies the evolution in time of some indicators that are representative for the touristic activity in Romania during 2000 – 2009, as well as correlations between them, these being: the number of arrivals and of overnights in the tourism structures with accomodation functions, as well as the number of tourism structures and their accomodation capacity, separately for foreign and Romanian visitors, as well as for different tourism destinations. All these indicators were extracted from the database of the National Institute of Statistics. Generally, an increase in time of the number of tourists is found, but also a certain decrease during the last two-three years, except for some groups of destinations which show a rather peculiar and interesting dynamics. Thus, the tourism in the resorts of the seaside area have registered an accentuated decrease during the last four years, especially for the foreign tourists, that reflects a change in their options. On the other hand, the tourism for the category of destination “other localities and touristic routes (which excludes the resorts of the spa, seaside, and mountain areas, as well as the city of Bucharest and all the county capital cities has shown a remarkable growth during the whole considered time interval, indicating an increase of the interest of the tourists (both Romanians and foreigners for the cultural and rural tourism.
Statistical analysis of long term spatial and temporal trends of ...
Indian Academy of Sciences (India)
The annual and seasonal trend analysis of different surface temperature parameters (average, maximum, minimum and diurnal temperature range) has been done for historical (1971–2005) and future periods (2011–2099) in the middle catchment of Sutlej river basin, India. The future time series of temperature data has ...
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...
Spatial statistical analysis of dissatisfaction with the performance of ...
African Journals Online (AJOL)
The analysis reveals spatial clustering in the level of dissatisfaction with the performance of local government. It also reveals percentage of respondents dissatisfied with dwelling, mean sense of safety index, and percentage agree the country is going in the wrong direction, as significant predictors of the level of local ...
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…
Statistical analysis of the organizational factors influence on the ...
African Journals Online (AJOL)
At the same time the research of working hours by means of photos of the working day, a moment observations method and the made time observations is important. Correlation dependence of workers' labor productivity on factors of the work organization is revealed. The analysis of the indicators directed to organizational ...
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
Solar spectra analysis based on the statistical moment method
Czech Academy of Sciences Publication Activity Database
Druckmüller, M.; Klvaňa, Miroslav; Druckmüllerová, Z.
2007-01-01
Roč. 31, č. 1 (2007), s. 297-307 ISSN 1845-8319. [Dynamical processes in the solar atmosphere. Hvar, 24.09.2006-29.09.2006] R&D Projects: GA ČR GA205/04/2129 Institutional research plan: CEZ:AV0Z10030501 Keywords : spectral analysis * method Subject RIV: BN - Astronomy, Celestial Mechanics, Astrophysics
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…
Directory of Open Access Journals (Sweden)
Ruslana Sushko
2015-08-01
Full Text Available Purpose: to identify the factors of efficiency of competitive activity of highly skilled basketball players at the stage of maximum realization of individual potential. Material and Methods: in order to identify the factors that have supported the performance of Ukraine's male national team in the European Championship, data analysis and generalization of scientific and technical literature and online data, analysis of official protocols of competitive activities, analysis and generalization of best pedagogical practices, pedagogical supervision, methods of mathematical statistics were used. Results: the efficiency of competitive activity of basketball players was analyzed using such indicators as team roles, won and lost matches, scored and missed points, technical, tactical and age indicators. Conclusions: the factors of efficiency of competitive activity of highly skilled basketball players at the stage of maximum realization of individual potential were identified with regard to age indicators
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.
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)
ON THE STATISTICAL ANALYSIS OF X-RAY POLARIZATION MEASUREMENTS
Energy Technology Data Exchange (ETDEWEB)
Strohmayer, T. E.; Kallman, T. R. [X-ray Astrophysics Lab, Astrophysics Science Division, NASA' s Goddard Space Flight Center, Greenbelt, MD 20771 (United States)
2013-08-20
In many polarimetry applications, including observations in the X-ray band, the measurement of a polarization signal can be reduced to the detection and quantification of a deviation from uniformity of a distribution of measured angles of the form A + Bcos {sup 2}({phi} - {phi}{sub 0}) (0 < {phi} < {pi}). We explore the statistics of such polarization measurements using Monte Carlo simulations and {chi}{sup 2} fitting methods. We compare our results to those derived using the traditional probability density used to characterize polarization measurements and quantify how they deviate as the intrinsic modulation amplitude grows. We derive relations for the number of counts required to reach a given detection level (parameterized by {beta} the ''number of {sigma}'s'' of the measurement) appropriate for measuring the modulation amplitude a by itself (single interesting parameter case) or jointly with the position angle {phi} (two interesting parameters case). We show that for the former case, when the intrinsic amplitude is equal to the well-known minimum detectable polarization, (MDP) it is, on average, detected at the 3{sigma} level. For the latter case, when one requires a joint measurement at the same confidence level, then more counts are needed than what was required to achieve the MDP level. This additional factor is amplitude-dependent, but is Almost-Equal-To 2.2 for intrinsic amplitudes less than about 20%. It decreases slowly with amplitude and is Almost-Equal-To 1.8 when the amplitude is 50%. We find that the position angle uncertainty at 1{sigma} confidence is well described by the relation {sigma}{sub {phi}} = 28. Degree-Sign 5/{beta}.
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.
A statistical analysis based recommender model for heart disease patients.
Mustaqeem, Anam; Anwar, Syed Muhammad; Khan, Abdul Rashid; Majid, Muhammad
2017-12-01
An intelligent information technology based system could have a positive impact on the life-style of patients suffering from chronic diseases by providing useful health recommendations. In this paper, we have proposed a hybrid model that provides disease prediction and medical recommendations to cardiac patients. The first part aims at implementing a prediction model, that can identify the disease of a patient and classify it into one of the four output classes i.e., non-cardiac chest pain, silent ischemia, angina, and myocardial infarction. Following the disease prediction, the second part of the model provides general medical recommendations to patients. The recommendations are generated by assessing the severity of clinical features of patients, estimating the risk associated with clinical features and disease, and calculating the probability of occurrence of disease. The purpose of this model is to build an intelligent and adaptive recommender system for heart disease patients. The experiments for the proposed recommender system are conducted on a clinical data set collected and labelled in consultation with medical experts from a known hospital. The performance of the proposed prediction model is evaluated using accuracy and kappa statistics as evaluation measures. The medical recommendations are generated based on information collected from a knowledge base created with the help of physicians. The results of the recommendation model are evaluated using confusion matrix and gives an accuracy of 97.8%. The proposed system exhibits good prediction and recommendation accuracies and promises to be a useful contribution in the field of e-health and medical informatics. Copyright © 2017 Elsevier B.V. All rights reserved.
Characterization of Nuclear Fuel using Multivariate Statistical Analysis
Energy Technology Data Exchange (ETDEWEB)
Robel, M; Robel, M; Robel, M; Kristo, M J; Kristo, M J
2007-11-27
Various combinations of reactor type and fuel composition have been characterized using principle components analysis (PCA) of the concentrations of 9 U and Pu isotopes in the 10 fuel as a function of burnup. The use of PCA allows the reduction of the 9-dimensional data (isotopic concentrations) into a 3-dimensional approximation, giving a visual representation of the changes in nuclear fuel composition with burnup. Real-world variation in the concentrations of {sup 234}U and {sup 236}U in the fresh (unirradiated) fuel was accounted for. The effects of reprocessing were also simulated. The results suggest that, 15 even after reprocessing, Pu isotopes can be used to determine both the type of reactor and the initial fuel composition with good discrimination. Finally, partial least squares discriminant analysis (PSLDA) was investigated as a substitute for PCA. Our results suggest that PLSDA is a better tool for this application where separation between known classes is most important.
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.
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
Statistical analysis of lead isotope data in provenance studies
International Nuclear Information System (INIS)
Reedy, C.L.
1991-01-01
This paper reports on tracing artifacts to ore sources which is different from assigning ore samples to time epochs. Until now, archaeometrists working with lead isotopes have used the ratio methods developed by geochronologists. For provenance studies, however, the use of composition data (the fraction of each of the four isotopes) leads to fewer arbitrary choices, two standard types of plots (labelled ternary and canonical variable, and a consistent method of discriminant analysis for separating groups of samples from different sources
Practical guidance for statistical analysis of operational event data
Energy Technology Data Exchange (ETDEWEB)
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.
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 results for chlorine in freshwater from BCR certification analyses by highly competent analytical laboratories in the EC. Titration showed systematic errors of several percent, while radiochemical neutron activation analysis produced results without detectable bias....
WebBUGS: Conducting Bayesian Statistical Analysis Online
Directory of Open Access Journals (Sweden)
Zhiyong Zhang
2014-11-01
Full Text Available A web interface, named WebBUGS, is developed to conduct Bayesian analysis online over the Internet through OpenBUGS and R. WebBUGS can be used with the minimum requirement of a web browser both remotely and locally. WebBUGS has many collaborative features such as email notification and sharing. WebBUGS also eases the use of OpenBUGS by providing built-in model templates, data management module, and other useful modules. In this paper, the use of WebBUGS is illustrated and discussed.
Directory of Open Access Journals (Sweden)
Żelazny Katarzyna
2015-01-01
Full Text Available During ship design, its service speed is one of the crucial parameters which decide on future economic effects. As sufficiently exact calculation methods applicable to preliminary design stage are lacking the so called contract speed which a ship reaches in calm water is usually applied. In the paper [11] a parametric method for calculation of total ship resistance in actual weather conditions (wind, waves, sea current, was presented. This paper presents a parametric model of ship propulsion system (screw propeller - propulsion engine as well as a calculation method, based on both models, of mean statistical value of ship service speed in seasonal weather conditions occurring on shipping lines. The method makes use of only basic design parameters and may be applied in preliminary design stage.
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.
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.)
Statistical analysis of the direct count method for enumerating bacteria.
Kirchman, D; Sigda, J; Kapuscinski, R; Mitchell, R
1982-08-01
The direct count method for enumerating bacteria in natural environments is widely used. This paper analyzes the sources of variation contributed by the various levels of the method: subsamples, filters, and microscope fields. Based on a nested analysis of variance, we show that most of the variance (less than 80%) is caused by the fields and that the filters contributed nearly all of the remaining variance. The replication at each of the levels determines the total cost and error of a measurement. We compared several sampling schemes, including an optimal strategy which gives the lowest possible variance for a given cost. We recommend that preparing one filter from one subsample is adequate only if the samples are closely spaced in time or distance; otherwise, one filter should be prepared from two or preferably three subsamples. This sampling scheme emphasizes the importance of the highest level of replication. Our analysis shows that the accuracy of the direct count method can be substantially improved (by 20 to 50%) without a large increase in cost when the proper degree of replication at each level is performed.
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.
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.
Abd-El-Fattah, Sabry M.
2005-01-01
A Partial Least Squares Path Analysis technique was used to test the effect of students' prior experience with computers, statistical self-efficacy, and computer anxiety on their achievement in an introductory statistics course. Computer Anxiety Rating Scale and Current Statistics Self-Efficacy Scale were administered to a sample of 64 first-year…
Warmenhoven, John; Harrison, Andrew; Robinson, Mark A; Vanrenterghem, Jos; Bargary, Norma; Smith, Richard; Cobley, Stephen; Draper, Conny; Donnelly, Cyril; Pataky, Todd
2018-03-21
To examine whether the Functional Data Analysis (FDA), Statistical Parametric Mapping (SPM) and Statistical non-Parametric Mapping (SnPM) hypothesis testing techniques differ in their ability to draw inferences in the context of a single, simple experimental design. The sample data used is cross-sectional (two-sample gender comparison) and evaluation of differences between statistical techniques used a combination of descriptive and qualitative assessments. FDA, SPM and SnPM t-tests were applied to sample data of twenty highly skilled male and female rowers, rowing at 32 strokes per minute in a single scull boat. Statistical differences for gender were assessed by applying two t-tests (one for each side of the boat). The t-statistic values were identical for all three methods (with the FDA t-statistic presented as an absolute measure). The critical t-statistics (t crit ) were very similar between the techniques, with SPM t crit providing a marginally higher t crit than the FDA and SnPM t crit values (which were identical). All techniques were successful in identifying consistent sections of the force waveform, where male and female rowers were shown to differ significantly (pparametric assumption of SPM, as well as contextual factors related to the type of waveform data to be analysed and the experimental research question of interest. Copyright © 2018. Published by Elsevier Ltd.
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.)
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
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 Analysis Methods for the fMRI Data
Directory of Open Access Journals (Sweden)
Huseyin Boyaci
2011-08-01
Full Text Available Functional magnetic resonance imaging (fMRI is a safe and non-invasive way to assess brain functions by using signal changes associated with brain activity. The technique has become a ubiquitous tool in basic, clinical and cognitive neuroscience. This method can measure little metabolism changes that occur in active part of the brain. We process the fMRI data to be able to find the parts of brain that are involve in a mechanism, or to determine the changes that occur in brain activities due to a brain lesion. In this study we will have an overview over the methods that are used for the analysis of fMRI data.
Statistical Analysis of Temple Orientation in Ancient India
Aller, Alba; Belmonte, Juan Antonio
2015-05-01
The great diversity of religions that have been followed in India for over 3000 years is the reason why there are hundreds of temples built to worship dozens of different divinities. In this work, more than one hundred temples geographically distributed over the whole Indian land have been analyzed, obtaining remarkable results. For this purpose, a deep analysis of the main deities who are worshipped in each of them, as well as of the different dynasties (or cultures) who built them has also been conducted. As a result, we have found that the main axes of the temples dedicated to Shiva seem to be oriented to the east cardinal point while those temples dedicated to Vishnu would be oriented to both the east and west cardinal points. To explain these cardinal directions we propose to look back to the origins of Hinduism. Besides these cardinal orientations, clear solar orientations have also been found, especially at the equinoctial declination.
Statistical Analysis of Magnetic Abrasive Finishing (MAF) On Surface Roughness
Givi, Mehrdad; Tehrani, Alireza Fadaei; Mohammadi, Aminollah
2010-06-01
Magnetic assisted finishing is one of the nontraditional methods of polishing that recently has been attractive for the researchers. This paper investigates the effects of some parameters such as rotational speed of the permanent magnetic pole, work gap between the permanent pole and the work piece, number of the cycles and the weight of the abrasive particles on aluminum surface plate finishing. The three levels full factorial method was used as the DOE technique (design of experiments) for studying the selected factors. Analysis of Variance (ANOVA) has been used to determine significant factors and also to obtain an equation based on data regression. Experimental results indicate that for a change in surface roughness ΔRa, number of cycles and working gap are found to be the most significant parameters followed by rotational speed and then weight of powders.
STATISTICAL ANALYSIS OF ACOUSTIC WAVE PARAMETERS NEAR SOLAR ACTIVE REGIONS
International Nuclear Information System (INIS)
Rabello-Soares, M. Cristina; Bogart, Richard S.; Scherrer, Philip H.
2016-01-01
In order to quantify the influence of magnetic fields on acoustic mode parameters and flows in and around active regions, we analyze the differences in the parameters in magnetically quiet regions nearby an active region (which we call “nearby regions”), compared with those of quiet regions at the same disk locations for which there are no neighboring active regions. We also compare the mode parameters in active regions with those in comparably located quiet regions. Our analysis is based on ring-diagram analysis of all active regions observed by the Helioseismic and Magnetic Imager (HMI) during almost five years. We find that the frequency at which the mode amplitude changes from attenuation to amplification in the quiet nearby regions is around 4.2 mHz, in contrast to the active regions, for which it is about 5.1 mHz. This amplitude enhacement (the “acoustic halo effect”) is as large as that observed in the active regions, and has a very weak dependence on the wave propagation direction. The mode energy difference in nearby regions also changes from a deficit to an excess at around 4.2 mHz, but averages to zero over all modes. The frequency difference in nearby regions increases with increasing frequency until a point at which the frequency shifts turn over sharply, as in active regions. However, this turnover occurs around 4.9 mHz, which is significantly below the acoustic cutoff frequency. Inverting the horizontal flow parameters in the direction of the neigboring active regions, we find flows that are consistent with a model of the thermal energy flow being blocked directly below the active region.
International Nuclear Information System (INIS)
Robeyns, J.; Parmentier, F.; Peeters, G.
2001-01-01
In the framework of safety analysis for the Belgian nuclear power plants and for the reload compatibility studies, Tractebel Energy Engineering (TEE) has developed, to define a 95/95 DNBR criterion, a statistical thermal design method based on the analytical full statistical approach: the Statistical Thermal Design Procedure (STDP). In that methodology, each DNBR value in the core assemblies is calculated with an adapted CHF (Critical Heat Flux) correlation implemented in the sub-channel code Cobra for core thermal hydraulic analysis. The uncertainties of the correlation are represented by the statistical parameters calculated from an experimental database. The main objective of a sub-channel analysis is to prove that in all class 1 and class 2 situations, the minimum DNBR (Departure from Nucleate Boiling Ratio) remains higher than the Safety Analysis Limit (SAL). The SAL value is calculated from the Statistical Design Limit (SDL) value adjusted with some penalties and deterministic factors. The search of a realistic value for the SDL is the objective of the statistical thermal design methods. In this report, we apply a full statistical approach to define the DNBR criterion or SDL (Statistical Design Limit) with the strict observance of the design criteria defined in the Standard Review Plan. The same statistical approach is used to define the expected number of rods experiencing DNB. (author)
Plasma Heating in Solar Microflares: Statistics and Analysis
Energy Technology Data Exchange (ETDEWEB)
Kirichenko, A. S.; Bogachev, S. A. [Lebedev Physical Institute of the Russian Academy of Sciences, Moscow, 119991 (Russian Federation)
2017-05-01
In this paper we present the results of an analysis of 481 weak solar flares, from A0.01 class flares to the B GOES class, that were observed during the period of extremely low solar activity from 2009 April to July. For all flares we measured the temperature of the plasma in the isothermal and two-temperature approximations and tried to fit its relationship with the X-ray class using exponential and power-law functions. We found that the whole temperature distribution in the range from A0.01 to X-class cannot be fit by one exponential function. The fitting for weak flares below A1.0 is significantly steeper than that for medium and large flares. The power-law approximation seems to be more reliable: the corresponding functions were found to be in good agreement with experimental data both for microflares and for normal flares. Our study predicts that evidence of plasma heating can be found in flares starting from the A0.0002 X-ray class. Weaker events presumably cannot heat the surrounding plasma. We also estimated emission measures for all flares studied and the thermal energy for 113 events.
The statistical analysis of energy release in small-scale coronal structures
Ulyanov, Artyom; Kuzin, Sergey; Bogachev, Sergey
We present the results of statistical analysis of impulsive flare-like brightenings, which numerously occur in the quiet regions of solar corona. For our study, we utilized high-cadence observations performed with two EUV-telescopes - TESIS/Coronas-Photon and AIA/SDO. In total, we processed 6 sequences of images, registered throughout the period between 2009 and 2013, covering the rising phase of the 24th solar cycle. Based on high-speed DEM estimation method, we developed a new technique to evaluate the main parameters of detected events (geometrical sizes, duration, temperature and thermal energy). We then obtained the statistical distributions of these parameters and examined their variations depending on the level of solar activity. The results imply that near the minimum of the solar cycle the energy release in quiet corona is mainly provided by small-scale events (nanoflares), whereas larger events (microflares) prevail on the peak of activity. Furthermore, we investigated the coronal conditions that had specified the formation and triggering of registered flares. By means of photospheric magnetograms obtained with MDI/SoHO and HMI/SDO instruments, we examined the topology of local magnetic fields at different stages: the pre-flare phase, the peak of intensity and the ending phase. To do so, we introduced a number of topological parameters including the total magnetic flux, the distance between magnetic sources and their mutual arrangement. The found correlation between the change of these parameters and the formation of flares may offer an important tool for application of flare forecasting.
Statistical analysis for validating ACO-KNN algorithm as feature selection in sentiment analysis
Ahmad, Siti Rohaidah; Yusop, Nurhafizah Moziyana Mohd; Bakar, Azuraliza Abu; Yaakub, Mohd Ridzwan
2017-10-01
This research paper aims to propose a hybrid of ant colony optimization (ACO) and k-nearest neighbor (KNN) algorithms as feature selections for selecting and choosing relevant features from customer review datasets. Information gain (IG), genetic algorithm (GA), and rough set attribute reduction (RSAR) were used as baseline algorithms in a performance comparison with the proposed algorithm. This paper will also discuss the significance test, which was used to evaluate the performance differences between the ACO-KNN, IG-GA, and IG-RSAR algorithms. This study evaluated the performance of the ACO-KNN algorithm using precision, recall, and F-score, which were validated using the parametric statistical significance tests. The evaluation process has statistically proven that this ACO-KNN algorithm has been significantly improved compared to the baseline algorithms. The evaluation process has statistically proven that this ACO-KNN algorithm has been significantly improved compared to the baseline algorithms. In addition, the experimental results have proven that the ACO-KNN can be used as a feature selection technique in sentiment analysis to obtain quality, optimal feature subset that can represent the actual data in customer review data.
Shiavi, Richard
2007-01-01
Introduction to Applied Statistical Signal Analysis is designed for the experienced individual with a basic background in mathematics, science, and computer. With this predisposed knowledge, the reader will coast through the practical introduction and move on to signal analysis techniques, commonly used in a broad range of engineering areas such as biomedical engineering, communications, geophysics, and speech.Introduction to Applied Statistical Signal Analysis intertwines theory and implementation with practical examples and exercises. Topics presented in detail include: mathematical
Application of Multivariable Statistical Techniques in Plant-wide WWTP Control Strategies Analysis
DEFF Research Database (Denmark)
Flores Alsina, Xavier; Comas, J.; Rodríguez-Roda, I.
2007-01-01
The main objective of this paper is to present the application of selected multivariable statistical techniques in plant-wide wastewater treatment plant (WWTP) control strategies analysis. In this study, cluster analysis (CA), principal component analysis/factor analysis (PCA/FA) and discriminant...
Modeling gallic acid production rate by empirical and statistical analysis
Directory of Open Access Journals (Sweden)
Bratati Kar
2000-01-01
Full Text Available For predicting the rate of enzymatic reaction empirical correlation based on the experimental results obtained under various operating conditions have been developed. Models represent both the activation as well as deactivation conditions of enzymatic hydrolysis and the results have been analyzed by analysis of variance (ANOVA. The tannase activity was found maximum at incubation time 5 min, reaction temperature 40ºC, pH 4.0, initial enzyme concentration 0.12 v/v, initial substrate concentration 0.42 mg/ml, ionic strength 0.2 M and under these optimal conditions, the maximum rate of gallic acid production was 33.49 mumoles/ml/min.Para predizer a taxa das reações enzimaticas uma correlação empírica baseada nos resultados experimentais foi desenvolvida. Os modelos representam a ativação e a desativativação da hydrolise enzimatica. Os resultados foram avaliados pela análise de variança (ANOVA. A atividade máxima da tannase foi obtida após 5 minutos de incubação, temperatura 40ºC, pH 4,0, concentração inicial da enzima de 0,12 v/v, concentração inicial do substrato 0,42 mg/ml, força iônica 0,2 M. Sob essas condições a taxa máxima de produção ácido galico foi de 33,49 µmoles/ml/min.
Processing and statistical analysis of soil-root images
Razavi, Bahar S.; Hoang, Duyen; Kuzyakov, Yakov
2016-04-01
Importance of the hotspots such as rhizosphere, the small soil volume that surrounds and is influenced by plant roots, calls for spatially explicit methods to visualize distribution of microbial activities in this active site (Kuzyakov and Blagodatskaya, 2015). Zymography technique has previously been adapted to visualize the spatial dynamics of enzyme activities in rhizosphere (Spohn and Kuzyakov, 2014). Following further developing of soil zymography -to obtain a higher resolution of enzyme activities - we aimed to 1) quantify the images, 2) determine whether the pattern (e.g. distribution of hotspots in space) is clumped (aggregated) or regular (dispersed). To this end, we incubated soil-filled rhizoboxes with maize Zea mays L. and without maize (control box) for two weeks. In situ soil zymography was applied to visualize enzymatic activity of β-glucosidase and phosphatase at soil-root interface. Spatial resolution of fluorescent images was improved by direct application of a substrate saturated membrane to the soil-root system. Furthermore, we applied "spatial point pattern analysis" to determine whether the pattern (e.g. distribution of hotspots in space) is clumped (aggregated) or regular (dispersed). Our results demonstrated that distribution of hotspots at rhizosphere is clumped (aggregated) compare to control box without plant which showed regular (dispersed) pattern. These patterns were similar in all three replicates and for both enzymes. We conclude that improved zymography is promising in situ technique to identify, analyze, visualize and quantify spatial distribution of enzyme activities in the rhizosphere. Moreover, such different patterns should be considered in assessments and modeling of rhizosphere extension and the corresponding effects on soil properties and functions. Key words: rhizosphere, spatial point pattern, enzyme activity, zymography, maize.
Statistical analysis of rockfall volume distributions: Implications for rockfall dynamics
Dussauge, Carine; Grasso, Jean-Robert; Helmstetter, AgnèS.
2003-06-01
We analyze the volume distribution of natural rockfalls on different geological settings (i.e., calcareous cliffs in the French Alps, Grenoble area, and granite Yosemite cliffs, California Sierra) and different volume ranges (i.e., regional and worldwide catalogs). Contrary to previous studies that included several types of landslides, we restrict our analysis to rockfall sources which originated on subvertical cliffs. For the three data sets, we find that the rockfall volumes follow a power law distribution with a similar exponent value, within error bars. This power law distribution was also proposed for rockfall volumes that occurred along road cuts. All these results argue for a recurrent power law distribution of rockfall volumes on subvertical cliffs, for a large range of rockfall sizes (102-1010 m3), regardless of the geological settings and of the preexisting geometry of fracture patterns that are drastically different on the three studied areas. The power law distribution for rockfall volumes could emerge from two types of processes. First, the observed power law distribution of rockfall volumes is similar to the one reported for both fragmentation experiments and fragmentation models. This argues for the geometry of rock mass fragment sizes to possibly control the rockfall volumes. This way neither cascade nor avalanche processes would influence the rockfall volume distribution. Second, without any requirement of scale-invariant quenched heterogeneity patterns, the rock mass dynamics can arise from avalanche processes driven by fluctuations of the rock mass properties, e.g., cohesion or friction angle. This model may also explain the power law distribution reported for landslides involving unconsolidated materials. We find that the exponent values of rockfall volume on subvertical cliffs, 0.5 ± 0.2, is significantly smaller than the 1.2 ± 0.3 value reported for mixed landslide types. This change of exponents can be driven by the material strength, which
Quantitative analysis and IBM SPSS statistics a guide for business and finance
Aljandali, Abdulkader
2016-01-01
This guide is for practicing statisticians and data scientists who use IBM SPSS for statistical analysis of big data in business and finance. This is the first of a two-part guide to SPSS for Windows, introducing data entry into SPSS, along with elementary statistical and graphical methods for summarizing and presenting data. Part I also covers the rudiments of hypothesis testing and business forecasting while Part II will present multivariate statistical methods, more advanced forecasting methods, and multivariate methods. IBM SPSS Statistics offers a powerful set of statistical and information analysis systems that run on a wide variety of personal computers. The software is built around routines that have been developed, tested, and widely used for more than 20 years. As such, IBM SPSS Statistics is extensively used in industry, commerce, banking, local and national governments, and education. Just a small subset of users of the package include the major clearing banks, the BBC, British Gas, British Airway...
Benchmark validation of statistical models: Application to mediation analysis of imagery and memory.
MacKinnon, David P; Valente, Matthew J; Wurpts, Ingrid C
2018-03-29
This article describes benchmark validation, an approach to validating a statistical model. According to benchmark validation, a valid model generates estimates and research conclusions consistent with a known substantive effect. Three types of benchmark validation-(a) benchmark value, (b) benchmark estimate, and (c) benchmark effect-are described and illustrated with examples. Benchmark validation methods are especially useful for statistical models with assumptions that are untestable or very difficult to test. Benchmark effect validation methods were applied to evaluate statistical mediation analysis in eight studies using the established effect that increasing mental imagery improves recall of words. Statistical mediation analysis led to conclusions about mediation that were consistent with established theory that increased imagery leads to increased word recall. Benchmark validation based on established substantive theory is discussed as a general way to investigate characteristics of statistical models and a complement to mathematical proof and statistical simulation. (PsycINFO Database Record (c) 2018 APA, all rights reserved).
Jamshidi, Kambiz; Salehi, Jawad A.
2005-05-01
This paper describes a study of the performance of various configurations for placing multiple optical amplifiers in a typical coherent ultrashort light pulse code-division multiple access (CULP-CDMA) communication system using the additive noise model. For this study, a comprehensive performance analysis was developed that takes into account multiple-access noise, noise due to optical amplifiers, and thermal noise using the saddle-point approximation technique. Prior to obtaining the overall system performance, the input/output statistical models for different elements of the system such as encoders/decoders,star coupler, and optical amplifiers were obtained. Performance comparisons between an ideal and lossless quantum-limited case and a typical CULP-CDMA with various losses exhibit more than 30 dB more power requirement to obtain the same bit-error rate (BER). Considering the saturation effect of optical amplifiers, this paper discusses an algorithm for amplifiers' gain setting in various stages of the network in order to overcome the nonlinear effects on signal modulation in optical amplifiers. Finally, using this algorithm,various configurations of multiple optical amplifiers in CULP-CDMA are discussed and the rules for the required optimum number of amplifiers are shown with their corresponding optimum locations to be implemented along the CULP-CDMA system.
Bayesian Statistics and Uncertainty Quantification for Safety Boundary Analysis in Complex Systems
He, Yuning; Davies, Misty Dawn
2014-01-01
The analysis of a safety-critical system often requires detailed knowledge of safe regions and their highdimensional non-linear boundaries. We present a statistical approach to iteratively detect and characterize the boundaries, which are provided as parameterized shape candidates. Using methods from uncertainty quantification and active learning, we incrementally construct a statistical model from only few simulation runs and obtain statistically sound estimates of the shape parameters for safety boundaries.
Eskiizmir, Görkem; Baskın, Yasemin; Yalçın, Femin; Ellidokuz, Hülya; Ferris, Robert L
2016-11-01
Radiotherapy is one of the main treatment modalities for early-stage glottic carcinoma. Unfortunately, local failure may occur in a group of cases with T1-T2 glottic carcinoma. This meta-analysis sought to determine risk factors for radiation failure in patients with early-stage glottic carcinoma. A systematic and comprehensive search was performed for related studies published between 1995 and 2014. The primary end-point was 5-year local control. Data extraction and analysis were performed using the software STATA/SE 13.1 for Windows. Twenty-seven studies were eligible. A higher risk of radiation failure was demonstrated in male patients [relative risk (RR): 0.927, pfailure, although a moderate to high interstudy heterogeneity was determined. A statistically significant contribution was not detected for age, presence of comorbidity, alcohol use or subglottic extension. This is the first meta-analysis which assessed the potential risk factors for radiation failure in patients with early-stage glottic carcinoma. Gender and pretreatment hemoglobin level are major influential factors associated with radiation failure in patients with early-stage glottic carcinoma. However, prospective, randomized clinical trials may permit better stratification of their relative contributions, and those who may benefit more from upfront surgery. Copyright © 2016 Elsevier Ltd. All rights reserved.
Compliance strategy for statistically based neutron overpower protection safety analysis methodology
International Nuclear Information System (INIS)
Holliday, E.; Phan, B.; Nainer, O.
2009-01-01
The methodology employed in the safety analysis of the slow Loss of Regulation (LOR) event in the OPG and Bruce Power CANDU reactors, referred to as Neutron Overpower Protection (NOP) analysis, is a statistically based methodology. Further enhancement to this methodology includes the use of Extreme Value Statistics (EVS) for the explicit treatment of aleatory and epistemic uncertainties, and probabilistic weighting of the initial core states. A key aspect of this enhanced NOP methodology is to demonstrate adherence, or compliance, with the analysis basis. This paper outlines a compliance strategy capable of accounting for the statistical nature of the enhanced NOP methodology. (author)
International Nuclear Information System (INIS)
EI-Shanshoury, G.I.
2011-01-01
Several statistical distributions are used to model various reliability and maintainability parameters. The applied distribution depends on the' nature of the data being analyzed. The presented paper deals with analysis of some statistical distributions used in reliability to reach the best fit of distribution analysis. The calculations rely on circuit quantity parameters obtained by using Relex 2009 computer program. The statistical analysis of ten different distributions indicated that Weibull distribution gives the best fit distribution for modeling the reliability of the data set of Temperature Alarm Circuit (TAC). However, the Exponential distribution is found to be the best fit distribution for modeling the failure rate
Directory of Open Access Journals (Sweden)
Kyung Wook Nam
2015-11-01
Full Text Available BackgroundThis study analyzed 100 consecutive patients with primary cutaneous melanoma over the course of 13 years to determine whether epidemiological differences correspond to different stages of the disease. We also investigated whether epidemiological characteristics affected the survival rate. Our results were compared with those of selected descriptive studies of melanoma in other East Asian populations, in order to determine whether cutaneous melanoma patterns are similar in East Asian populations.MethodsThe patients' medical records were reviewed retrospectively, and we analyzed the relationship of epidemiological characteristics to staging and survival rate. Additionally, papers from Hong Kong and Japan describing these phenomena in East Asian populations were subjected to a statistical comparison.ResultsThe ratio of males to females was 1:1.8, and the foot was the most frequent tumor site (49%. Acral lentiginous melanoma occurred most frequently (55%. Nodular melanoma was associated with a higher stage. Stage III-IV tumors with Clark levels of IV-V were significantly associated with a low survival rate. A statistical analysis of comparable papers reported in Hong Kong and Japan showed similar results with regard to age, tumor location, and histopathological subtypes.ConclusionsThis study provides the first full epidemiological description of 100 consecutive cases of primary cutaneous melanoma in Korea, with results similar to those observed in other East Asian populations. Corresponding to previous findings, nodular melanoma tended to occur at a higher stage than other types, and tumors with high Clark levels and high stages showed a lower survival rate.
Capaccioni, Bruno; Valentini, Laura; Rocchi, Marco B. L.; Nappi, Giovanni; Sarocchi, Damiano
Computer-assisted image analysis can be successfully used to derive quantitative textural data on pyroclastic rock samples. This method provides a large number of different measurements such as grain size, particle shape and 2D orientation of particle main axes (directional- or shape-fabric) automatically and in a relatively short time. Orientation data reduction requires specific statistical tests, mainly devoted to defining the kind of particle distribution pattern, the possible occurrence of preferred particle orientation, the confidence interval of the mean direction and the degree of randomness with respect to pre-assigned theoretical frequency distributions. Data obtained from image analysis of seven lithified ignimbrite samples from the Vulsini Volcanic District (Central Italy) are used to test different statistics and to provide insight about directional fabrics. First, the possible occurrence of a significant deviation from a theoretical circular uniform distribution was evaluated by using the Rayleigh and Tukey χ2 tests. Then, the Kuiper test was performed to evaluate whether or not the observation fits with a unimodal, Von Mises-like theoretical frequency distribution. Finally, the confidence interval of mean direction was calculated. With the exception of one sample (FPD10), which showed a well-developed bimodality, all the analysed samples display significant anisotropic and unimodal distributions. The minimum number of measurements necessary to obtain reasonable variabilities of the calculated statistics and mean directions was evaluated by repeating random collections of the measured particles at increments of 100 particles for each sample. Although the observed variabilities depend largely on the pattern of distribution and an absolute minimum number cannot be stated, approximately 1500-2000 measurements are required in order to get meaningful mean directions for the analysed samples.
Valledor, Luis; Romero-Rodríguez, M Cristina; Jorrin-Novo, Jesus V
2014-01-01
Two-dimensional gel electrophoresis remains the most widely used technique for protein separation in plant proteomics experiments. Despite the continuous technical advances and improvements in current 2-DE protocols, an adequate and correct experimental design and statistical analysis of the data tend to be ignored or not properly documented in current literature. Both proper experimental design and appropriate statistical analysis are requested in order to confidently discuss our results and to conclude from experimental data.In this chapter, we describe a model procedure for a correct experimental design and a complete statistical analysis of proteomic dataset. Our model procedure covers all of the steps in data mining and processing, starting with the data preprocessing (transformation, missing value imputation, definition of outliers) and univariate statistics (parametric and nonparametric tests), and finishing with multivariate statistics (clustering, heat-mapping, PCA, ICA, PLS-DA).
Integrated Data Collection Analysis (IDCA) Program - Statistical Analysis of RDX Standard Data Sets
Energy Technology Data Exchange (ETDEWEB)
Sandstrom, Mary M. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Brown, Geoffrey W. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Preston, Daniel N. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Pollard, Colin J. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Warner, Kirstin F. [Naval Surface Warfare Center (NSWC), Indian Head, MD (United States). Indian Head Division; Sorensen, Daniel N. [Naval Surface Warfare Center (NSWC), Indian Head, MD (United States). Indian Head Division; Remmers, Daniel L. [Naval Surface Warfare Center (NSWC), Indian Head, MD (United States). Indian Head Division; Phillips, Jason J. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Shelley, Timothy J. [Air Force Research Lab. (AFRL), Tyndall AFB, FL (United States); Reyes, Jose A. [Applied Research Associates, Tyndall AFB, FL (United States); Hsu, Peter C. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Reynolds, John G. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
2015-10-30
The Integrated Data Collection Analysis (IDCA) program is conducting a Proficiency Test for Small- Scale Safety and Thermal (SSST) testing of homemade explosives (HMEs). Described here are statistical analyses of the results for impact, friction, electrostatic discharge, and differential scanning calorimetry analysis of the RDX Type II Class 5 standard. The material was tested as a well-characterized standard several times during the proficiency study to assess differences among participants and the range of results that may arise for well-behaved explosive materials. The analyses show that there are detectable differences among the results from IDCA participants. While these differences are statistically significant, most of them can be disregarded for comparison purposes to assess potential variability when laboratories attempt to measure identical samples using methods assumed to be nominally the same. The results presented in this report include the average sensitivity results for the IDCA participants and the ranges of values obtained. The ranges represent variation about the mean values of the tests of between 26% and 42%. The magnitude of this variation is attributed to differences in operator, method, and environment as well as the use of different instruments that are also of varying age. The results appear to be a good representation of the broader safety testing community based on the range of methods, instruments, and environments included in the IDCA Proficiency Test.
A new statistic for the analysis of circular data in gamma-ray astronomy
Protheroe, R. J.
1985-01-01
A new statistic is proposed for the analysis of circular data. The statistic is designed specifically for situations where a test of uniformity is required which is powerful against alternatives in which a small fraction of the observations is grouped in a small range of directions, or phases.
Measuring the Success of an Academic Development Programme: A Statistical Analysis
Smith, L. C.
2009-01-01
This study uses statistical analysis to estimate the impact of first-year academic development courses in microeconomics, statistics, accountancy, and information systems, offered by the University of Cape Town's Commerce Academic Development Programme, on students' graduation performance relative to that achieved by mainstream students. The data…
Development of statistical analysis code for meteorological data (W-View)
International Nuclear Information System (INIS)
Tachibana, Haruo; Sekita, Tsutomu; Yamaguchi, Takenori
2003-03-01
A computer code (W-View: Weather View) was developed to analyze the meteorological data statistically based on 'the guideline of meteorological statistics for the safety analysis of nuclear power reactor' (Nuclear Safety Commission on January 28, 1982; revised on March 29, 2001). The code gives statistical meteorological data to assess the public dose in case of normal operation and severe accident to get the license of nuclear reactor operation. This code was revised from the original code used in a large office computer code to enable a personal computer user to analyze the meteorological data simply and conveniently and to make the statistical data tables and figures of meteorology. (author)
PROSA: A computer program for statistical analysis of near-real-time-accountancy (NRTA) data
International Nuclear Information System (INIS)
Beedgen, R.; Bicking, U.
1987-04-01
The computer program PROSA (Program for Statistical Analysis of NRTA Data) is a tool to decide on the basis of statistical considerations if, in a given sequence of materials balance periods, a loss of material might have occurred or not. The evaluation of the material balance data is based on statistical test procedures. In PROSA three truncated sequential tests are applied to a sequence of material balances. The manual describes the statistical background of PROSA and how to use the computer program on an IBM-PC with DOS 3.1. (orig.) [de
Elimination of statistical fluctuations in higher order moments from event-by-event analysis
International Nuclear Information System (INIS)
Li Bo; Zhu Hongli; Liu Lianshou
2004-01-01
In the present investigation of high energy multiparticle production, the method of event by event analysis has received wide interest. Inasmuch as the limited number of particles in a single event, an important problem is that the elimination of statistical fluctuations has to be worked out first of all. In the current literature, the elimination of statistical fluctuations has been only considered in lower order moments (not above the third order). In the present paper, the elimination of statistical fluctuations is studied in higher order moments and a general expression for the elimination of statistical fluctuations in the moments of arbitrary order is given. (author)
Statistical analysis and optimization in the process/device/circuit/system microelectronics design
Kuleshov, A.; Nelayev, V.; Stempitsky, V.
2010-01-01
Methodology and results of statistical analysis and optimization in the joined process/device/circuit/system microelectronics design are presented. A simple example of the cell inverter design illustrates the e±ciency of the methodology.
Martin, David; Boyle, Fergal
2015-09-01
Several clinical studies have identified a strong correlation between neointimal hyperplasia following coronary stent deployment and both stent-induced arterial injury and altered vessel hemodynamics. As such, the sequential structural and fluid dynamics analysis of balloon-expandable stent deployment should provide a comprehensive indication of stent performance. Despite this observation, very few numerical studies of balloon-expandable coronary stents have considered both the mechanical and hemodynamic impact of stent deployment. Furthermore, in the few studies that have considered both phenomena, only a small number of stents have been considered. In this study, a sequential structural and fluid dynamics analysis methodology was employed to compare both the mechanical and hemodynamic impact of six balloon-expandable coronary stents. To investigate the relationship between stent design and performance, several common stent design properties were then identified and the dependence between these properties and both the mechanical and hemodynamic variables of interest was evaluated using statistical measures of correlation. Following the completion of the numerical analyses, stent strut thickness was identified as the only common design property that demonstrated a strong dependence with either the mean equivalent stress predicted in the artery wall or the mean relative residence time predicted on the luminal surface of the artery. These results corroborate the findings of the large-scale ISAR-STEREO clinical studies and highlight the crucial role of strut thickness in coronary stent design. The sequential structural and fluid dynamics analysis methodology and the multivariable statistical treatment of the results described in this study should prove useful in the design of future balloon-expandable coronary stents.
On the importance of statistics in breath analysis - Hope or curse?
Eckel, Sandrah P.; Baumbach, Jan; Hauschild, Anne-Christin
2014-01-01
As we saw at the 2013 Breath Analysis Summit, breath analysis is a rapidly evolving field. Increasingly sophisticated technology is producing huge amounts of complex data. A major barrier now faced by the breath research community is the analysis of these data. Emerging breath data require sophisticated, modern statistical methods to allow for a careful and robust deduction of real-world conclusions.
Rahimi, Elham; Maghsoudi, Abbas; Hezarkhani, Ardeshir
2016-12-01
The Kashmar-Kerman volcano-plutonic arc in central Iran is an important mining province and hosts several large deposits of magmatic iron ores. Some of these ores are characterized by considerable amounts of REE-bearing minerals like apatite, monazite, and xenotime. The Lakehsiyah iron-apatite deposits in the Bafq district (central Iran), are hosted by late Precambrian-Cambrian igneous and dolomite rocks. In order to investigate geochemical characteristics of the rare earth elements related to their genesis, statistical analysis was carried out. The Interpretation of these data led to the identification of four different zones as follows: iron ore, phosphate rich, metasomatic and host rock. Chemical analysis of the zones shows high LREE/HREE ratio with a considerable negative Eu anomaly being a characteristic of the Kiruna ore-type. The distribution of REE patterns resembles, but in different contents, indicating a genetic relationship, and a similar source of magnetite and apatite ores that are similar to most of the iron-apatite deposits in central Iran. Two generations of apatite (type-I and II) are recognized, including coarse-grained euhedral crystals (type-I) and fine grained crystals (type- II) present in the matrix. Apatite-Ι shows a heterogeneous pattern which consists of dark and light phases due to variable concentrations of REE and traces of Si, Na, and Cl. The REEs enrichment explains the presence of monazite and xenotime inclusions within dark apatite grains being a result of hydrothermal activity. The final stage of the hydrothermal system was accompanied by gold overprinting with minor iron ore during metasomatism, probably driven from a deep-seated intrusion, usually found along micro-fractures cutting the previously formed minerals.
Statistical analysis and Monte Carlo simulation of growing self-avoiding walks on percolation
Energy Technology Data Exchange (ETDEWEB)
Zhang Yuxia [Department of Physics, Wuhan University, Wuhan 430072 (China); Sang Jianping [Department of Physics, Wuhan University, Wuhan 430072 (China); Department of Physics, Jianghan University, Wuhan 430056 (China); Zou Xianwu [Department of Physics, Wuhan University, Wuhan 430072 (China)]. E-mail: xwzou@whu.edu.cn; Jin Zhunzhi [Department of Physics, Wuhan University, Wuhan 430072 (China)
2005-09-26
The two-dimensional growing self-avoiding walk on percolation was investigated by statistical analysis and Monte Carlo simulation. We obtained the expression of the mean square displacement and effective exponent as functions of time and percolation probability by statistical analysis and made a comparison with simulations. We got a reduced time to scale the motion of walkers in growing self-avoiding walks on regular and percolation lattices.
Directory of Open Access Journals (Sweden)
Н. В. Лещук
2017-12-01
Full Text Available Purpose. To define statistical methods and tools (application packages for creating the decision support system (DSS for qualifying examination of plant varieties suitable for dissemination (VSD in the context of data processing tasks. To substantiate the selection of software for processing statistical data relative to field and laboratory investigations that are included into the qualifying examination for VSD. Methods. Analytical one based on the comparison of methods of descriptive and multivariate statistics and tools of intellectual analysis of data obtained during qualifying examination for VSD. Comparative analysis of software tools for processing statistical data in order to prepare proposals for the final decision on plant variety application. Decomposition of tasks was carried out which were included into the decision support system for qualifying examination of varieties-candidates for VSD. Results. Statistical package SPSS, analysis package included in MS Excel and programe language R was compared for the following criteria: interface usability, functionality, quality of calculation result presentation, visibility of graphical information, software cost. The both packages were widely used in the world for statistical data processing, they have similar functions for statistics calculation. Conclusion. Tasks of VSD were separated and recommended to tackle using investigated tools. Programe language R was a product recommended to use as a tool. The main advantage of R as compared to the package IBM SPSS Statistics is the fact that R is an open source software.
TRAPR: R Package for Statistical Analysis and Visualization of RNA-Seq Data.
Lim, Jae Hyun; Lee, Soo Youn; Kim, Ju Han
2017-03-01
High-throughput transcriptome sequencing, also known as RNA sequencing (RNA-Seq), is a standard technology for measuring gene expression with unprecedented accuracy. Numerous bioconductor packages have been developed for the statistical analysis of RNA-Seq data. However, these tools focus on specific aspects of the data analysis pipeline, and are difficult to appropriately integrate with one another due to their disparate data structures and processing methods. They also lack visualization methods to confirm the integrity of the data and the process. In this paper, we propose an R-based RNA-Seq analysis pipeline called TRAPR, an integrated tool that facilitates the statistical analysis and visualization of RNA-Seq expression data. TRAPR provides various functions for data management, the filtering of low-quality data, normalization, transformation, statistical analysis, data visualization, and result visualization that allow researchers to build customized analysis pipelines.
Performance of real-time elastography for the staging of hepatic fibrosis: a meta-analysis.
Directory of Open Access Journals (Sweden)
Huisuo Hong
Full Text Available BACKGROUND: With the rapid development of real-time elastography (RTE, a variety of measuring methods have been developed for the assessment of hepatic fibrosis. We evaluated the overall performance of four methods based on RTE by performing meta-analysis of published literature. METHODS: Online journal databases and a manual search from April 2000 to April 2014 were used. Studies from different databases that meet inclusion criteria were enrolled. The statistical analysis was performed using a random-effects model and fixed-effects model for the overall effectiveness of RTE. The area under the receiver operating characteristic curve (AUROC was calculated for various means. Fagan plot analysis was used to estimate the clinical utility of RTE, and the heterogeneity of the studies was explored with meta-regression analysis. RESULTS: Thirteen studies from published articles were enrolled and analyzed. The combined AUROC of the liver fibrosis index (LFI for the evaluation of significant fibrosis (F≥2, advanced fibrosis (F≥3, and cirrhosis (F = 4 were 0.79, 0.94, and 0.85, respectively. The AUROC of the elasticity index (EI ranged from 0.75 to 0.92 for F≥2 and 0.66 to 0.85 for F = 4. The overall AUROC of the elastic ratio of the liver for the intrahepatic venous vessels were 0.94, 0.93, and 0.96, respectively. The AUROC of the elastic ratio of the liver for the intercostal muscle in diagnosing advanced fibrosis and cirrhosis were 0.96 and 0.92, respectively. There was significant heterogeneity in the diagnostic odds ratio (DOR for F≥2 of LFI mainly due to etiology (p<0.01. CONCLUSION: The elastic ratio of the liver for the intrahepatic vein has excellent precision in differentiating each stage of hepatic fibrosis and is recommend to be applied to the clinic.
Statistical trend analysis methodology for rare failures in changing technical systems
International Nuclear Information System (INIS)
Ott, K.O.; Hoffmann, H.J.
1983-07-01
A methodology for a statistical trend analysis (STA) in failure rates is presented. It applies primarily to relatively rare events in changing technologies or components. The formulation is more general and the assumptions are less restrictive than in a previously published version. Relations of the statistical analysis and probabilistic assessment (PRA) are discussed in terms of categorization of decisions for action following particular failure events. The significance of tentatively identified trends is explored. In addition to statistical tests for trend significance, a combination of STA and PRA results quantifying the trend complement is proposed. The STA approach is compared with other concepts for trend characterization. (orig.)
R: A Software Environment for Comprehensive Statistical Analysis of Astronomical Data
Feigelson, E. D.
2012-09-01
R is the largest public domain software language for statistical analysis of data. Together with CRAN, its rapidly growing collection of >3000 add-on specialized packages, it implements around 60,000 statistical functionalities in a cohesive software environment. Extensive graphical capabilities and interfaces with other programming languages are also available. The scope and language of R/CRAN are briefly described, along with efforts to promulgate its use in the astronomy. R can become an important tool for advanced statistical analysis of astronomical data.
What type of statistical model to choose for the analysis of radioimmunoassays
International Nuclear Information System (INIS)
Huet, S.
1984-01-01
The current techniques used for statistical analysis of radioimmunoassays are not very satisfactory for either the statistician or the biologist. They are based on an attempt to make the response curve linear to avoid complicated computations. The present article shows that this practice has considerable effects (often neglected) on the statistical assumptions which must be formulated. A more strict analysis is proposed by applying the four-parameter logistic model. The advantages of this method are: the statistical assumptions formulated are based on observed data, and the model can be applied to almost all radioimmunoassays [fr
Yang, Jie; McArdle, Conor; Daniels, Stephen
2014-01-01
A Similarity Ratio Analysis (SRA) method is proposed for early-stage Fault Detection (FD) in plasma etching processes using real-time Optical Emission Spectrometer (OES) data as input. The SRA method can help to realise a highly precise control system by detecting abnormal etch-rate faults in real-time during an etching process. The method processes spectrum scans at successive time points and uses a windowing mechanism over the time series to alleviate problems with timing uncertainties due to process shift from one process run to another. A SRA library is first built to capture features of a healthy etching process. By comparing with the SRA library, a Similarity Ratio (SR) statistic is then calculated for each spectrum scan as the monitored process progresses. A fault detection mechanism, named 3-Warning-1-Alarm (3W1A), takes the SR values as inputs and triggers a system alarm when certain conditions are satisfied. This design reduces the chance of false alarm, and provides a reliable fault reporting service. The SRA method is demonstrated on a real semiconductor manufacturing dataset. The effectiveness of SRA-based fault detection is evaluated using a time-series SR test and also using a post-process SR test. The time-series SR provides an early-stage fault detection service, so less energy and materials will be wasted by faulty processing. The post-process SR provides a fault detection service with higher reliability than the time-series SR, but with fault testing conducted only after each process run completes.
Directory of Open Access Journals (Sweden)
Jie Yang
Full Text Available A Similarity Ratio Analysis (SRA method is proposed for early-stage Fault Detection (FD in plasma etching processes using real-time Optical Emission Spectrometer (OES data as input. The SRA method can help to realise a highly precise control system by detecting abnormal etch-rate faults in real-time during an etching process. The method processes spectrum scans at successive time points and uses a windowing mechanism over the time series to alleviate problems with timing uncertainties due to process shift from one process run to another. A SRA library is first built to capture features of a healthy etching process. By comparing with the SRA library, a Similarity Ratio (SR statistic is then calculated for each spectrum scan as the monitored process progresses. A fault detection mechanism, named 3-Warning-1-Alarm (3W1A, takes the SR values as inputs and triggers a system alarm when certain conditions are satisfied. This design reduces the chance of false alarm, and provides a reliable fault reporting service. The SRA method is demonstrated on a real semiconductor manufacturing dataset. The effectiveness of SRA-based fault detection is evaluated using a time-series SR test and also using a post-process SR test. The time-series SR provides an early-stage fault detection service, so less energy and materials will be wasted by faulty processing. The post-process SR provides a fault detection service with higher reliability than the time-series SR, but with fault testing conducted only after each process run completes.
Directory of Open Access Journals (Sweden)
Vedat Sağlam
2015-01-01
Full Text Available The aim of this paper is to analyze a tandem queueing model with two stages. The arrivals to the first stage are Poisson stream and the service time at this stage is exponential. There is no waiting room at first stage. The service time is hyperexponential and no waiting is allowed at second stage. The transition probabilities and loss probabilities of this model are obtained. In addition, the loss probability at second stage is optimized. Performance measures and the variance of the numbers of customers of this tandem queueing model are found. It is seen that the numbers of customers in first stage and second stage are dependent. Finally we have simulated this queueing model. For different values of parameters, exact values, simulated values, and optimal values of obtained performance measures of this model are numerically shown in tables and graphs.
Pestman, Wiebe R
2009-01-01
This textbook provides a broad and solid introduction to mathematical statistics, including the classical subjects hypothesis testing, normal regression analysis, and normal analysis of variance. In addition, non-parametric statistics and vectorial statistics are considered, as well as applications of stochastic analysis in modern statistics, e.g., Kolmogorov-Smirnov testing, smoothing techniques, robustness and density estimation. For students with some elementary mathematical background. With many exercises. Prerequisites from measure theory and linear algebra are presented.
The Statistical Analysis and Assessment of the Solvency of Forest Enterprises
Directory of Open Access Journals (Sweden)
Vyniatynska Liudmila V.
2016-05-01
Full Text Available The aim of the article is to conduct a statistical analysis of the solvency of forest enterprises through a system of statistical indicators using the sampling method (the sampling is based on the criteria of forest cover percent of regions of Ukraine. Using financial statements of forest enterprises that form a system of information and analytical support for the statistical analysis of the level of solvency of forestry in Ukraine for 2009-2015 has been analyzed and evaluated. With the help of the developed recommended values the results of the statistical analysis of the forest enterprises’ solvency under conditions of self-financing and commercial consideration have been summarized and systematized. Using the methodology of the statistical analysis of the forest enterprises’ solvency conducted on the corresponding conceptual framework, which is relevant and meets the current needs, a system of statistical indicators enabling to assess the level of solvency of forest enterprises and identify the reasons of its low level has been calculated.
Directory of Open Access Journals (Sweden)
Goovaerts Pierre
2011-12-01
Full Text Available Abstract Background Although prostate cancer-related incidence and mortality have declined recently, striking racial/ethnic differences persist in the United States. Visualizing and modelling temporal trends of prostate cancer late-stage incidence, and how they vary according to geographic locations and race, should help explaining such disparities. Joinpoint regression is increasingly used to identify the timing and extent of changes in time series of health outcomes. Yet, most analyses of temporal trends are aspatial and conducted at the national level or for a single cancer registry. Methods Time series (1981-2007 of annual proportions of prostate cancer late-stage cases were analyzed for non-Hispanic Whites and non-Hispanic Blacks in each county of Florida. Noise in the data was first filtered by binomial kriging and results were modelled using joinpoint regression. A similar analysis was also conducted at the state level and for groups of metropolitan and non-metropolitan counties. Significant racial differences were detected using tests of parallelism and coincidence of time trends. A new disparity statistic was introduced to measure spatial and temporal changes in the frequency of racial disparities. Results State-level percentage of late-stage diagnosis decreased 50% since 1981; a decline that accelerated in the 90's when Prostate Specific Antigen (PSA screening was introduced. Analysis at the metropolitan and non-metropolitan levels revealed that the frequency of late-stage diagnosis increased recently in urban areas, and this trend was significant for white males. The annual rate of decrease in late-stage diagnosis and the onset years for significant declines varied greatly among counties and racial groups. Most counties with non-significant average annual percent change (AAPC were located in the Florida Panhandle for white males, whereas they clustered in South-eastern Florida for black males. The new disparity statistic indicated
Goovaerts, Pierre; Xiao, Hong
2011-12-05
Although prostate cancer-related incidence and mortality have declined recently, striking racial/ethnic differences persist in the United States. Visualizing and modelling temporal trends of prostate cancer late-stage incidence, and how they vary according to geographic locations and race, should help explaining such disparities. Joinpoint regression is increasingly used to identify the timing and extent of changes in time series of health outcomes. Yet, most analyses of temporal trends are aspatial and conducted at the national level or for a single cancer registry. Time series (1981-2007) of annual proportions of prostate cancer late-stage cases were analyzed for non-Hispanic Whites and non-Hispanic Blacks in each county of Florida. Noise in the data was first filtered by binomial kriging and results were modelled using joinpoint regression. A similar analysis was also conducted at the state level and for groups of metropolitan and non-metropolitan counties. Significant racial differences were detected using tests of parallelism and coincidence of time trends. A new disparity statistic was introduced to measure spatial and temporal changes in the frequency of racial disparities. State-level percentage of late-stage diagnosis decreased 50% since 1981; a decline that accelerated in the 90's when Prostate Specific Antigen (PSA) screening was introduced. Analysis at the metropolitan and non-metropolitan levels revealed that the frequency of late-stage diagnosis increased recently in urban areas, and this trend was significant for white males. The annual rate of decrease in late-stage diagnosis and the onset years for significant declines varied greatly among counties and racial groups. Most counties with non-significant average annual percent change (AAPC) were located in the Florida Panhandle for white males, whereas they clustered in South-eastern Florida for black males. The new disparity statistic indicated that the spatial extent of racial disparities reached a
Statistical power analysis a simple and general model for traditional and modern hypothesis tests
Murphy, Kevin R; Wolach, Allen
2014-01-01
Noted for its accessible approach, this text applies the latest approaches of power analysis to both null hypothesis and minimum-effect testing using the same basic unified model. Through the use of a few simple procedures and examples, the authors show readers with little expertise in statistical analysis how to obtain the values needed to carry out the power analysis for their research. Illustrations of how these analyses work and how they can be used to choose the appropriate criterion for defining statistically significant outcomes are sprinkled throughout. The book presents a simple and g
Design, analysis and testing of a novel decoupled 2-DOF flexure-based micropositioning stage
Yang, Shang; Chen, Weihai; Liu, Jingmeng; Chen, Wenjie
2017-09-01
This paper presents the design, analysis and testing of a novel decoupled 2-DOF flexure-based micropositioning stage driven by piezoelectric-actuators (PZTs). In order to enlarge the travel range, a Scott-Russell mechanism and leverage mechanism are arranged in series, constituting a two-grade displacement amplifier to conquer the small displacement of the PZT. The design micropositioning stage is composed of symmetrically distributed flexure modules and each flexure module comprises compound parallelogram flexure beams serving as input decoupling, which allows the output decoupling by employing the tridimensional double compound parallelogram flexure mechanism. Based on the analytical model of both the amplifier and the XY stage established in static and dynamic analysis, the dimensions and performance of the stage has been conducted, which are verified by finite element analysis with ANSYS Workbench and prototype experiment with the fabricated prototype of the designed stage. It can be seen that the workspace of the developed stage is 148.11~μ \\text{m}× 149.73~μ m with the maximum output coupling errors of 0.693% and 0.637% in the y and x directions. The experimental results demonstrate that the proposed micropositioning stage possesses good performance in trajectory tracking and can achieve a wide range of precise positioning.
DEFF Research Database (Denmark)
Jones, Allan; Sommerlund, Bo
2007-01-01
The uses of null hypothesis significance testing (NHST) and statistical power analysis within psychological research are critically discussed. The article looks at the problems of relying solely on NHST when dealing with small and large sample sizes. The use of power-analysis in estimating...
Analysis of Variance with Summary Statistics in Microsoft® Excel®
Larson, David A.; Hsu, Ko-Cheng
2010-01-01
Students regularly are asked to solve Single Factor Analysis of Variance problems given only the sample summary statistics (number of observations per category, category means, and corresponding category standard deviations). Most undergraduate students today use Excel for data analysis of this type. However, Excel, like all other statistical…
STATISTICAL ANALYSIS OF DIESEL CAR REPAIRS ON THE EXAMPLE OF DIESEL SERVICE ADAMCZYK COMPANIES
Directory of Open Access Journals (Sweden)
Łukasz KONIECZNY
2014-12-01
Full Text Available The article presents a statistical analysis of car repair data gathered by an examined company over five-year time interval. It is based on a SQL database which contains information about all realized orders. The analysis defines the structure of the set of repaired car makes and additionally to find the most frequent vehicle defects.
On the blind use of statistical tools in the analysis of globular cluster stars
D'Antona, Francesca; Caloi, Vittoria; Tailo, Marco
2018-04-01
As with most data analysis methods, the Bayesian method must be handled with care. We show that its application to determine stellar evolution parameters within globular clusters can lead to paradoxical results if used without the necessary precautions. This is a cautionary tale on the use of statistical tools for big data analysis.
PVeStA: A Parallel Statistical Model Checking and Quantitative Analysis Tool
AlTurki, Musab
2011-01-01
Statistical model checking is an attractive formal analysis method for probabilistic systems such as, for example, cyber-physical systems which are often probabilistic in nature. This paper is about drastically increasing the scalability of statistical model checking, and making such scalability of analysis available to tools like Maude, where probabilistic systems can be specified at a high level as probabilistic rewrite theories. It presents PVeStA, an extension and parallelization of the VeStA statistical model checking tool [10]. PVeStA supports statistical model checking of probabilistic real-time systems specified as either: (i) discrete or continuous Markov Chains; or (ii) probabilistic rewrite theories in Maude. Furthermore, the properties that it can model check can be expressed in either: (i) PCTL/CSL, or (ii) the QuaTEx quantitative temporal logic. As our experiments show, the performance gains obtained from parallelization can be very high. © 2011 Springer-Verlag.
DEFF Research Database (Denmark)
Edjabou, Maklawe Essonanawe; Martín-Fernández, Josep Antoni; Scheutz, Charlotte
2017-01-01
Data for fractional solid waste composition provide relative magnitudes of individual waste fractions, the percentages of which always sum to 100, thereby connecting them intrinsically. Due to this sum constraint, waste composition data represent closed data, and their interpretation and analysis......, have the potential to generate spurious or misleading results. Therefore, ¨compositional data should be transformed adequately prior to any statistical analysis, such as computing mean, standard deviation and correlation coefficients....... require statistical methods, other than classical statistics that are suitable only for non-constrained data such as absolute values. However, the closed characteristics of waste composition data are often ignored when analysed. The results of this study showed, for example, that unavoidable animal...... and plastic packaging. However, correlation tests applied to waste fraction compositions (percentage values) showed a negative association in this regard, thus demonstrating that statistical analyses applied to compositional waste fraction data, without addressing the closed characteristics of these data...
Introduction to statistics and data analysis with exercises, solutions and applications in R
Heumann, Christian; Shalabh
2016-01-01
This introductory statistics textbook conveys the essential concepts and tools needed to develop and nurture statistical thinking. It presents descriptive, inductive and explorative statistical methods and guides the reader through the process of quantitative data analysis. In the experimental sciences and interdisciplinary research, data analysis has become an integral part of any scientific study. Issues such as judging the credibility of data, analyzing the data, evaluating the reliability of the obtained results and finally drawing the correct and appropriate conclusions from the results are vital. The text is primarily intended for undergraduate students in disciplines like business administration, the social sciences, medicine, politics, macroeconomics, etc. It features a wealth of examples, exercises and solutions with computer code in the statistical programming language R as well as supplementary material that will enable the reader to quickly adapt all methods to their own applications.