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Methods For Statistical Data Analysis Of Multivariate Observations

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Methods For Statistical Data Analysis Of Multivariate Observations

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Author : R. Gnanadesikan
language : en
Publisher: John Wiley & Sons
Release Date : 2011-01-25

Methods For Statistical Data Analysis Of Multivariate Observations written by R. Gnanadesikan and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-01-25 with Mathematics categories.

A practical guide for multivariate statistical techniques-- nowupdated and revised In recent years, innovations in computer technology and statisticalmethodologies have dramatically altered the landscape ofmultivariate data analysis. This new edition of Methods forStatistical Data Analysis of Multivariate Observations explorescurrent multivariate concepts and techniques while retaining thesame practical focus of its predecessor. It integrates methods anddata-based interpretations relevant to multivariate analysis in away that addresses real-world problems arising in many areas ofinterest. Greatly revised and updated, this Second Edition provides helpfulexamples, graphical orientation, numerous illustrations, and anappendix detailing statistical software, including the S (or Splus)and SAS systems. It also offers * An expanded chapter on cluster analysis that covers advances inpattern recognition * New sections on inputs to clustering algorithms and aids forinterpreting the results of cluster analysis * An exploration of some new techniques of summarization andexposure * New graphical methods for assessing the separations among theeigenvalues of a correlation matrix and for comparing sets ofeigenvectors * Knowledge gained from advances in robust estimation anddistributional models that are slightly broader than themultivariate normal This Second Edition is invaluable for graduate students, appliedstatisticians, engineers, and scientists wishing to usemultivariate techniques in a variety of disciplines.

Methods For Statistical Data Analysis Of Multivariate Observations

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Author : R. Gnanadesikan
language : en
Publisher:
Release Date : 1997-05-01

Methods For Statistical Data Analysis Of Multivariate Observations written by R. Gnanadesikan and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1997-05-01 with Multivariate analysis categories.

Methods For Statistical Data Analysis Of Multivariate Observations

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Author : R. Gnanadesikan
language : en
Publisher: John Wiley & Sons
Release Date : 1997-02-04

Methods For Statistical Data Analysis Of Multivariate Observations

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Author : Ram Gnanadesikan
language : en
Publisher: John Wiley & Sons
Release Date : 1977

Methods For Statistical Data Analysis Of Multivariate Observations written by Ram Gnanadesikan and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 1977 with Mathematics categories.

A practical guide for multivariate statistical techniques- now updated and revised In recent years, innovations in computer technology and statistical methodologies have dramatically altered the landscape of multivariate data analysis. This new edition of Methods for Statistical Data Analysis of Multivariate Observations explores current multivariate concepts and techniques while retaining the same practical focus of its predecessor. It integrates methods and data-based interpretations relevant to multivariate analysis in a way that addresses real-world problems arising in many areas of interest. Greatly revised and updated, this Second Edition provides helpful examples, graphical orientation, numerous illustrations, and an appendix detailing statistical software, including the S (or Splus) and SAS systems. It also offers An expanded chapter on cluster analysis that covers advances in pattern recognition New sections on inputs to clustering algorithms and aids for interpreting the results of cluster analysis An exploration of some new techniques of summarization and exposure New graphical methods for assessing the separations among the eigenvalues of a correlation matrix and for comparing sets of eigenvectors Knowledge gained from advances in robust estimation and distributional models that are slightly broader than the multivariate normal This Second Edition is invaluable for graduate students, applied statisticians, engineers, and scientists wishing to use multivariate techniques in a variety of disciplines.

Statistical Data Analysis

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Author : Ram Gnanadesikan
language : en
Publisher: American Mathematical Soc.
Release Date : 1983-12-31

Statistical Data Analysis written by Ram Gnanadesikan and has been published by American Mathematical Soc. this book supported file pdf, txt, epub, kindle and other format this book has been release on 1983-12-31 with Mathematics categories.

Simulation And The Monte Carlo Method

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Author : Reuven Y. Rubinstein
language : en
Publisher: John Wiley & Sons
Release Date : 2011-09-20

Simulation And The Monte Carlo Method written by Reuven Y. Rubinstein and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-09-20 with Mathematics categories.

This accessible new edition explores the major topics in Monte Carlo simulation Simulation and the Monte Carlo Method, Second Edition reflects the latest developments in the field and presents a fully updated and comprehensive account of the major topics that have emerged in Monte Carlo simulation since the publication of the classic First Edition over twenty-five years ago. While maintaining its accessible and intuitive approach, this revised edition features a wealth of up-to-date information that facilitates a deeper understanding of problem solving across a wide array of subject areas, such as engineering, statistics, computer science, mathematics, and the physical and life sciences. The book begins with a modernized introduction that addresses the basic concepts of probability, Markov processes, and convex optimization. Subsequent chapters discuss the dramatic changes that have occurred in the field of the Monte Carlo method, with coverage of many modern topics including: Markov Chain Monte Carlo Variance reduction techniques such as the transform likelihood ratio method and the screening method The score function method for sensitivity analysis The stochastic approximation method and the stochastic counter-part method for Monte Carlo optimization The cross-entropy method to rare events estimation and combinatorial optimization Application of Monte Carlo techniques for counting problems, with an emphasis on the parametric minimum cross-entropy method An extensive range of exercises is provided at the end of each chapter, with more difficult sections and exercises marked accordingly for advanced readers. A generous sampling of applied examples is positioned throughout the book, emphasizing various areas of application, and a detailed appendix presents an introduction to exponential families, a discussion of the computational complexity of stochastic programming problems, and sample MATLAB programs. Requiring only a basic, introductory knowledge of probability and statistics, Simulation and the Monte Carlo Method, Second Edition is an excellent text for upper-undergraduate and beginning graduate courses in simulation and Monte Carlo techniques. The book also serves as a valuable reference for professionals who would like to achieve a more formal understanding of the Monte Carlo method.

Spatial Statistics

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Author : Brian D. Ripley
language : en
Publisher: John Wiley & Sons
Release Date : 2005-02-25

Spatial Statistics written by Brian D. Ripley and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-02-25 with Mathematics categories.

The Wiley-Interscience Paperback Series consists of selected booksthat have been made more accessible to consumers in an effort toincrease global appeal and general circulation. With these newunabridged softcover volumes, Wiley hopes to extend the lives ofthese works by making them available to future generations ofstatisticians, mathematicians, and scientists. "Books such as this that bring together, clarify, and summarizerecent research can lead to a great increase of interest in thearea. . . . a major achievement in describing many aspects ofspatial data and discussing, with examples, different methods ofanalysis." –Royal Statistical Society "Dr. Ripley’s book is an excellent survey of the spatialstatistical methodology. It is very well illustrated with examples[that] give a clear view of the wide scope of the subject, the wayin which techniques often have to be tailored to particularapplications, and the different sorts of spatial data thatarise." –The Bulletin of the London Mathematics Society Spatial Statistics provides a comprehensive guide to theanalysis of spatial data. Each chapter covers a particular dataformat and the associated class of problems, introducing theory,giving computational suggestions, and providing examples. Methodsare illustrated by computer-drawn figures. The book serves as anintroduction to this rapidly growing research area formathematicians and statisticians, and as a reference to newcomputer methods for researchers in ecology, geology, archaeology,and the earth sciences.

Statistical Methods For The Assessment Of Point Source Pollution

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Author : D.T. Chapman
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06

Statistical Methods For The Assessment Of Point Source Pollution written by D.T. Chapman and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Mathematics categories.

This book contains the proceedings of a workshop, 'Statistical Methods for the Assess ment of Point Source Pollution', held September 12-14, 1988, at the Canada Centre for Inland Waters in Burlington, Ontario, Canada. The objectives of the workshop were to: a) advance the art, science, and application of statistical methods to current water quality issues by stimulating discussions and disseminating ideas and information. The emphasis was on statistical problems associated with monitor ing and controlling discharges from industries and municipalities and assessing the impact of these discharges on receiving water quality, b) provide a forum for managers, engineers, scientists, and statisticians to present and discuss techniques for evaluating water quality data and planning monitoring activities, c) provide a published state-of-the art summary of the application of statistical methods for the assessment of point source discharges and their impact on water qUality. The papers contained in this volume cover a number of topics that are of concern not only for monitoring and assessing point source pollution but also for other environmental problems.

Weibull Models

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Author : D. N. Prabhakar Murthy
language : en
Publisher: John Wiley & Sons
Release Date : 2004-01-28

Weibull Models written by D. N. Prabhakar Murthy and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004-01-28 with Mathematics categories.

A comprehensive perspective on Weibull models The literature on Weibull models is vast, disjointed, andscattered across many different journals. Weibull Models is acomprehensive guide that integrates all the different facets ofWeibull models in a single volume. This book will be of great help to practitioners in reliabilityand other disciplines in the context of modeling data sets usingWeibull models. For researchers interested in these modelingtechniques, exercises at the end of each chapter define potentialtopics for future research. Organized into seven distinct parts, Weibull Models: * Covers model analysis, parameter estimation, model validation,and application * Serves as both a handbook and a research monograph. As ahandbook, it classifies the different models and presents theirproperties. As a research monograph, it unifies the literature andpresents the results in an integrated manner * Intertwines theory and application * Focuses on model identification prior to model parameterestimation * Discusses the usefulness of the Weibull Probability plot (WPP)in the model selection to model a given data set * Highlights the use of Weibull models in reliability theory Filled with in-depth analysis, Weibull Models pulls together themost relevant information on this topic to give everyone fromreliability engineers to applied statisticians involved withreliability and survival analysis a clear look at what Weibullmodels can offer.

Applied Bayesian Modeling And Causal Inference From Incomplete Data Perspectives

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Author : Andrew Gelman
language : en
Publisher: John Wiley & Sons
Release Date : 2004-09-03

Applied Bayesian Modeling And Causal Inference From Incomplete Data Perspectives written by Andrew Gelman and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004-09-03 with Mathematics categories.

This book brings together a collection of articles on statistical methods relating to missing data analysis, including multiple imputation, propensity scores, instrumental variables, and Bayesian inference. Covering new research topics and real-world examples which do not feature in many standard texts. The book is dedicated to Professor Don Rubin (Harvard). Don Rubin has made fundamental contributions to the study of missing data. Key features of the book include: Comprehensive coverage of an imporant area for both research and applications. Adopts a pragmatic approach to describing a wide range of intermediate and advanced statistical techniques. Covers key topics such as multiple imputation, propensity scores, instrumental variables and Bayesian inference. Includes a number of applications from the social and health sciences. Edited and authored by highly respected researchers in the area.

Methods For Statistical Data Analysis Of Multivariate Observations

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