Nonparametric Statistical Inference

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Nonparametric Statistical Inference

Author : Jean Dickinson Gibbons
Publisher : CRC Press
ISBN 13 : 1439896127
Total Pages : 652 pages
Book Rating : 4.4/5 (398 download)

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Book Synopsis Nonparametric Statistical Inference by : Jean Dickinson Gibbons

Download or read book Nonparametric Statistical Inference written by Jean Dickinson Gibbons and published by CRC Press. This book was released on 2010-07-26 with total page 652 pages. Available in PDF, EPUB and Kindle. Book excerpt: Proven Material for a Course on the Introduction to the Theory and/or on the Applications of Classical Nonparametric Methods Since its first publication in 1971, Nonparametric Statistical Inference has been widely regarded as the source for learning about nonparametric statistics. The fifth edition carries on this tradition while thoroughly revising at least 50 percent of the material. New to the Fifth Edition Updated and revised contents based on recent journal articles in the literature A new section in the chapter on goodness-of-fit tests A new chapter that offers practical guidance on how to choose among the various nonparametric procedures covered Additional problems and examples Improved computer figures This classic, best-selling statistics book continues to cover the most commonly used nonparametric procedures. The authors carefully state the assumptions, develop the theory behind the procedures, and illustrate the techniques using realistic research examples from the social, behavioral, and life sciences. For most procedures, they present the tests of hypotheses, confidence interval estimation, sample size determination, power, and comparisons of other relevant procedures. The text also gives examples of computer applications based on Minitab, SAS, and StatXact and compares these examples with corresponding hand calculations. The appendix includes a collection of tables required for solving the data-oriented problems. Nonparametric Statistical Inference, Fifth Edition provides in-depth yet accessible coverage of the theory and methods of nonparametric statistical inference procedures. It takes a practical approach that draws on scores of examples and problems and minimizes the theorem-proof format. Jean Dickinson Gibbons was recently interviewed regarding her generous pledge to Virginia Tech.

Nonparametric Statistical Inference

Author : Jean Dickinson Gibbons
Publisher : CRC Press
ISBN 13 : 0824755227
Total Pages : 676 pages
Book Rating : 4.8/5 (247 download)

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Book Synopsis Nonparametric Statistical Inference by : Jean Dickinson Gibbons

Download or read book Nonparametric Statistical Inference written by Jean Dickinson Gibbons and published by CRC Press. This book was released on 2003-05 with total page 676 pages. Available in PDF, EPUB and Kindle. Book excerpt: Thoroughly revised and reorganized, the fourth edition presents in-depth coverage of the theory and methods of the most widely used nonparametric procedures in statistical analysis and offers example applications appropriate for all areas of the social, behavioral, and life sciences. The book presents new material on the quantiles, the calculation of exact and simulated power, multiple comparisons, additional goodness-of-fit tests, methods of analysis of count data, and modern computer applications using MINITAB, SAS, and STATXACT. It includes tabular guides for simplified applications of tests and finding P values and confidence interval estimates.

All of Nonparametric Statistics

Author : Larry Wasserman
Publisher : Springer Science & Business Media
ISBN 13 : 0387306234
Total Pages : 272 pages
Book Rating : 4.3/5 (873 download)

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Book Synopsis All of Nonparametric Statistics by : Larry Wasserman

Download or read book All of Nonparametric Statistics written by Larry Wasserman and published by Springer Science & Business Media. This book was released on 2006-09-10 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: This text provides the reader with a single book where they can find accounts of a number of up-to-date issues in nonparametric inference. The book is aimed at Masters or PhD level students in statistics, computer science, and engineering. It is also suitable for researchers who want to get up to speed quickly on modern nonparametric methods. It covers a wide range of topics including the bootstrap, the nonparametric delta method, nonparametric regression, density estimation, orthogonal function methods, minimax estimation, nonparametric confidence sets, and wavelets. The book’s dual approach includes a mixture of methodology and theory.

Nonparametric Statistical Inference

Author : Jean Dickinson Gibbons
Publisher : CRC Press
ISBN 13 : 135161617X
Total Pages : 695 pages
Book Rating : 4.3/5 (516 download)

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Book Synopsis Nonparametric Statistical Inference by : Jean Dickinson Gibbons

Download or read book Nonparametric Statistical Inference written by Jean Dickinson Gibbons and published by CRC Press. This book was released on 2020-12-21 with total page 695 pages. Available in PDF, EPUB and Kindle. Book excerpt: Praise for previous editions: "... a classic with a long history." – Statistical Papers "The fact that the first edition of this book was published in 1971 ... [is] testimony to the book’s success over a long period." – ISI Short Book Reviews "... one of the best books available for a theory course on nonparametric statistics. ... very well written and organized ... recommended for teachers and graduate students." – Biometrics "... There is no competitor for this book and its comprehensive development and application of nonparametric methods. Users of one of the earlier editions should certainly consider upgrading to this new edition." – Technometrics "... Useful to students and research workers ... a good textbook for a beginning graduate-level course in nonparametric statistics." – Journal of the American Statistical Association Since its first publication in 1971, Nonparametric Statistical Inference has been widely regarded as the source for learning about nonparametrics. The Sixth Edition carries on this tradition and incorporates computer solutions based on R. Features Covers the most commonly used nonparametric procedures States the assumptions, develops the theory behind the procedures, and illustrates the techniques using realistic examples from the social, behavioral, and life sciences Presents tests of hypotheses, confidence-interval estimation, sample size determination, power, and comparisons of competing procedures Includes an Appendix of user-friendly tables needed for solutions to all data-oriented examples Gives examples of computer applications based on R, MINITAB, STATXACT, and SAS Lists over 100 new references Nonparametric Statistical Inference, Sixth Edition, has been thoroughly revised and rewritten to make it more readable and reader-friendly. All of the R solutions are new and make this book much more useful for applications in modern times. It has been updated throughout and contains 100 new citations, including some of the most recent, to make it more current and useful for researchers.

Nonparametric Measures of Association

Author : Jean Dickinson Gibbons
Publisher : SAGE
ISBN 13 : 9780803946644
Total Pages : 108 pages
Book Rating : 4.9/5 (466 download)

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Book Synopsis Nonparametric Measures of Association by : Jean Dickinson Gibbons

Download or read book Nonparametric Measures of Association written by Jean Dickinson Gibbons and published by SAGE. This book was released on 1993-02-25 with total page 108 pages. Available in PDF, EPUB and Kindle. Book excerpt: Aimed at helping the researcher select the most appropriate measure of association for two or more variables, the author clearly describes such techniques as Spearman's rho, Kendall's tau, Goodman and Kruskals' gamma and Somer's d and carefully explains the calculation procedures as well as the substantive meaning of each measure.

Parametric and Nonparametric Inference from Record-Breaking Data

Author : Sneh Gulati
Publisher : Springer Science & Business Media
ISBN 13 : 9780387001388
Total Pages : 132 pages
Book Rating : 4.0/5 (13 download)

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Book Synopsis Parametric and Nonparametric Inference from Record-Breaking Data by : Sneh Gulati

Download or read book Parametric and Nonparametric Inference from Record-Breaking Data written by Sneh Gulati and published by Springer Science & Business Media. This book was released on 2003-01-27 with total page 132 pages. Available in PDF, EPUB and Kindle. Book excerpt: By providing a comprehensive look at statistical inference from record-breaking data in both parametric and nonparametric settings, this book treats the area of nonparametric function estimation from such data in detail. Its main purpose is to fill this void on general inference from record values. Statisticians, mathematicians, and engineers will find the book useful as a research reference. It can also serve as part of a graduate-level statistics or mathematics course.

Bootstrapping

Author : Christopher Z. Mooney
Publisher : SAGE
ISBN 13 : 9780803953819
Total Pages : 84 pages
Book Rating : 4.9/5 (538 download)

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Book Synopsis Bootstrapping by : Christopher Z. Mooney

Download or read book Bootstrapping written by Christopher Z. Mooney and published by SAGE. This book was released on 1993-08-09 with total page 84 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book is. . . clear and well-written. . . anyone with any interest in the basis of quantitative analysis simply must read this book. . . . well-written, with a wealth of explanation. . ." --Dougal Hutchison in Educational Research Using real data examples, this volume shows how to apply bootstrapping when the underlying sampling distribution of a statistic cannot be assumed normal, as well as when the sampling distribution has no analytic solution. In addition, it discusses the advantages and limitations of four bootstrap confidence interval methods--normal approximation, percentile, bias-corrected percentile, and percentile-t. The book concludes with a convenient summary of how to apply this computer-intensive methodology using various available software packages.

Nonparametric Statistical Methods

Author : Myles Hollander
Publisher : John Wiley & Sons
ISBN 13 : 1118553292
Total Pages : 872 pages
Book Rating : 4.1/5 (185 download)

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Book Synopsis Nonparametric Statistical Methods by : Myles Hollander

Download or read book Nonparametric Statistical Methods written by Myles Hollander and published by John Wiley & Sons. This book was released on 2013-11-25 with total page 872 pages. Available in PDF, EPUB and Kindle. Book excerpt: Praise for the Second Edition “This book should be an essential part of the personal library of every practicing statistician.”—Technometrics Thoroughly revised and updated, the new edition of Nonparametric Statistical Methods includes additional modern topics and procedures, more practical data sets, and new problems from real-life situations. The book continues to emphasize the importance of nonparametric methods as a significant branch of modern statistics and equips readers with the conceptual and technical skills necessary to select and apply the appropriate procedures for any given situation. Written by leading statisticians, Nonparametric Statistical Methods, Third Edition provides readers with crucial nonparametric techniques in a variety of settings, emphasizing the assumptions underlying the methods. The book provides an extensive array of examples that clearly illustrate how to use nonparametric approaches for handling one- or two-sample location and dispersion problems, dichotomous data, and one-way and two-way layout problems. In addition, the Third Edition features: The use of the freely available R software to aid in computation and simulation, including many new R programs written explicitly for this new edition New chapters that address density estimation, wavelets, smoothing, ranked set sampling, and Bayesian nonparametrics Problems that illustrate examples from agricultural science, astronomy, biology, criminology, education, engineering, environmental science, geology, home economics, medicine, oceanography, physics, psychology, sociology, and space science Nonparametric Statistical Methods, Third Edition is an excellent reference for applied statisticians and practitioners who seek a review of nonparametric methods and their relevant applications. The book is also an ideal textbook for upper-undergraduate and first-year graduate courses in applied nonparametric statistics.

Nonparametric Statistical Tests

Author : Markus Neuhauser
Publisher : CRC Press
ISBN 13 : 1439867046
Total Pages : 247 pages
Book Rating : 4.4/5 (398 download)

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Book Synopsis Nonparametric Statistical Tests by : Markus Neuhauser

Download or read book Nonparametric Statistical Tests written by Markus Neuhauser and published by CRC Press. This book was released on 2011-12-19 with total page 247 pages. Available in PDF, EPUB and Kindle. Book excerpt: Nonparametric Statistical Tests: A Computational Approach describes classical nonparametric tests, as well as novel and little-known methods such as the Baumgartner-Weiss-Schindler and the Cucconi tests. The book presents SAS and R programs, allowing readers to carry out the different statistical methods, such as permutation and bootstrap tests. Th

Parametric and Nonparametric Inference for Statistical Dynamic Shape Analysis with Applications

Author : Chiara Brombin
Publisher : Springer
ISBN 13 : 9783319263106
Total Pages : 115 pages
Book Rating : 4.2/5 (631 download)

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Book Synopsis Parametric and Nonparametric Inference for Statistical Dynamic Shape Analysis with Applications by : Chiara Brombin

Download or read book Parametric and Nonparametric Inference for Statistical Dynamic Shape Analysis with Applications written by Chiara Brombin and published by Springer. This book was released on 2016-02-19 with total page 115 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book considers specific inferential issues arising from the analysis of dynamic shapes with the attempt to solve the problems at hand using probability models and nonparametric tests. The models are simple to understand and interpret and provide a useful tool to describe the global dynamics of the landmark configurations. However, because of the non-Euclidean nature of shape spaces, distributions in shape spaces are not straightforward to obtain. The book explores the use of the Gaussian distribution in the configuration space, with similarity transformations integrated out. Specifically, it works with the offset-normal shape distribution as a probability model for statistical inference on a sample of a temporal sequence of landmark configurations. This enables inference for Gaussian processes from configurations onto the shape space. The book is divided in two parts, with the first three chapters covering material on the offset-normal shape distribution, and the remaining chapters covering the theory of NonParametric Combination (NPC) tests. The chapters offer a collection of applications which are bound together by the theme of this book. They refer to the analysis of data from the FG-NET (Face and Gesture Recognition Research Network) database with facial expressions. For these data, it may be desirable to provide a description of the dynamics of the expressions, or testing whether there is a difference between the dynamics of two facial expressions or testing which of the landmarks are more informative in explaining the pattern of an expression.

Nonparametric Inference on Manifolds

Author : Abhishek Bhattacharya
Publisher : Cambridge University Press
ISBN 13 : 1107019583
Total Pages : 252 pages
Book Rating : 4.1/5 (7 download)

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Book Synopsis Nonparametric Inference on Manifolds by : Abhishek Bhattacharya

Download or read book Nonparametric Inference on Manifolds written by Abhishek Bhattacharya and published by Cambridge University Press. This book was released on 2012-04-05 with total page 252 pages. Available in PDF, EPUB and Kindle. Book excerpt: Ideal for statisticians, this book will also interest probabilists, mathematicians, computer scientists, and morphometricians with mathematical training. It presents a systematic introduction to a general nonparametric theory of statistics on manifolds, with emphasis on manifolds of shapes. The theory has important applications in medical diagnostics, image analysis and machine vision.

Robust Nonparametric Statistical Methods

Author : Thomas P. Hettmansperger
Publisher : John Wiley & Sons
ISBN 13 :
Total Pages : 492 pages
Book Rating : 4.F/5 ( download)

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Book Synopsis Robust Nonparametric Statistical Methods by : Thomas P. Hettmansperger

Download or read book Robust Nonparametric Statistical Methods written by Thomas P. Hettmansperger and published by John Wiley & Sons. This book was released on 1998 with total page 492 pages. Available in PDF, EPUB and Kindle. Book excerpt: Offering an alternative to traditional statistical procedures which are based on least squares fitting, the authors cover such topics as one and two sample location models, linear models, and multivariate models. Both theory and applications are examined.

All of Statistics

Author : Larry Wasserman
Publisher : Springer Science & Business Media
ISBN 13 : 0387217363
Total Pages : 446 pages
Book Rating : 4.3/5 (872 download)

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Book Synopsis All of Statistics by : Larry Wasserman

Download or read book All of Statistics written by Larry Wasserman and published by Springer Science & Business Media. This book was released on 2013-12-11 with total page 446 pages. Available in PDF, EPUB and Kindle. Book excerpt: Taken literally, the title "All of Statistics" is an exaggeration. But in spirit, the title is apt, as the book does cover a much broader range of topics than a typical introductory book on mathematical statistics. This book is for people who want to learn probability and statistics quickly. It is suitable for graduate or advanced undergraduate students in computer science, mathematics, statistics, and related disciplines. The book includes modern topics like non-parametric curve estimation, bootstrapping, and classification, topics that are usually relegated to follow-up courses. The reader is presumed to know calculus and a little linear algebra. No previous knowledge of probability and statistics is required. Statistics, data mining, and machine learning are all concerned with collecting and analysing data.

Nonparametric Statistics

Author : Jean D. Gibbons
Publisher : SAGE Publications, Incorporated
ISBN 13 : 9780803939516
Total Pages : 96 pages
Book Rating : 4.9/5 (395 download)

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Book Synopsis Nonparametric Statistics by : Jean D. Gibbons

Download or read book Nonparametric Statistics written by Jean D. Gibbons and published by SAGE Publications, Incorporated. This book was released on 1992-10-07 with total page 96 pages. Available in PDF, EPUB and Kindle. Book excerpt: Through the use of actual research investigations that have appeared in recent social science journals, Gibbons shows the reader the specific methodology and logical rationale for many of the best-known and most frequently used nonparametric methods that are applicable to most small and large sample sizes. The methods are organized according to the type of sample structure that produced the data to be analyzed, and the inference types covered are limited to location tests, such as the sign test, the Mann-Whitney-Wilcoxon test, the Kruskal-Wallis test and Friedman's test. The formal introduction of each test is followed by a data example, calculated first by hand and then by computer.

Statistical Inference Based on Divergence Measures

Author : Leandro Pardo
Publisher : CRC Press
ISBN 13 : 1420034812
Total Pages : 513 pages
Book Rating : 4.4/5 (2 download)

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Book Synopsis Statistical Inference Based on Divergence Measures by : Leandro Pardo

Download or read book Statistical Inference Based on Divergence Measures written by Leandro Pardo and published by CRC Press. This book was released on 2018-11-12 with total page 513 pages. Available in PDF, EPUB and Kindle. Book excerpt: The idea of using functionals of Information Theory, such as entropies or divergences, in statistical inference is not new. However, in spite of the fact that divergence statistics have become a very good alternative to the classical likelihood ratio test and the Pearson-type statistic in discrete models, many statisticians remain unaware of this p

A Parametric Approach to Nonparametric Statistics

Author : Mayer Alvo
Publisher : Springer
ISBN 13 : 3319941534
Total Pages : 277 pages
Book Rating : 4.3/5 (199 download)

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Book Synopsis A Parametric Approach to Nonparametric Statistics by : Mayer Alvo

Download or read book A Parametric Approach to Nonparametric Statistics written by Mayer Alvo and published by Springer. This book was released on 2018-10-12 with total page 277 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book demonstrates that nonparametric statistics can be taught from a parametric point of view. As a result, one can exploit various parametric tools such as the use of the likelihood function, penalized likelihood and score functions to not only derive well-known tests but to also go beyond and make use of Bayesian methods to analyze ranking data. The book bridges the gap between parametric and nonparametric statistics and presents the best practices of the former while enjoying the robustness properties of the latter. This book can be used in a graduate course in nonparametrics, with parts being accessible to senior undergraduates. In addition, the book will be of wide interest to statisticians and researchers in applied fields.

Nonparametric Statistics with Applications to Science and Engineering

Author : Paul H. Kvam
Publisher : John Wiley & Sons
ISBN 13 : 9780470168691
Total Pages : 448 pages
Book Rating : 4.1/5 (686 download)

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Book Synopsis Nonparametric Statistics with Applications to Science and Engineering by : Paul H. Kvam

Download or read book Nonparametric Statistics with Applications to Science and Engineering written by Paul H. Kvam and published by John Wiley & Sons. This book was released on 2007-08-24 with total page 448 pages. Available in PDF, EPUB and Kindle. Book excerpt: A thorough and definitive book that fully addresses traditional and modern-day topics of nonparametric statistics This book presents a practical approach to nonparametric statistical analysis and provides comprehensive coverage of both established and newly developed methods. With the use of MATLAB, the authors present information on theorems and rank tests in an applied fashion, with an emphasis on modern methods in regression and curve fitting, bootstrap confidence intervals, splines, wavelets, empirical likelihood, and goodness-of-fit testing. Nonparametric Statistics with Applications to Science and Engineering begins with succinct coverage of basic results for order statistics, methods of categorical data analysis, nonparametric regression, and curve fitting methods. The authors then focus on nonparametric procedures that are becoming more relevant to engineering researchers and practitioners. The important fundamental materials needed to effectively learn and apply the discussed methods are also provided throughout the book. Complete with exercise sets, chapter reviews, and a related Web site that features downloadable MATLAB applications, this book is an essential textbook for graduate courses in engineering and the physical sciences and also serves as a valuable reference for researchers who seek a more comprehensive understanding of modern nonparametric statistical methods.