Nonparametric Statistical Inference

Author : Jean Dickinson Gibbons,Subhabrata Chakraborti
Publisher : CRC Press
Page : 695 pages
File Size : 49,9 Mb
Release : 2020-12-21
Category : Mathematics
ISBN : 9781351616171

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Nonparametric Statistical Inference by Jean Dickinson Gibbons,Subhabrata Chakraborti Pdf

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.

Author : Jean Dickinson Gibbons,Subhabrata Chakraborti
Publisher : CRC Press
Page : 652 pages
File Size : 55,7 Mb
Release : 2010-07-26
Category : Mathematics
ISBN : 9781439896129

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Nonparametric Statistical Inference by Jean Dickinson Gibbons,Subhabrata Chakraborti Pdf

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.

Author : Jean Dickinson Gibbons,Subhabrata Chakraborti
Publisher : CRC Press
Page : 350 pages
File Size : 49,7 Mb
Release : 2014-03-10
Category : Mathematics
ISBN : 9781135532017

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Nonparametric Statistical Inference by Jean Dickinson Gibbons,Subhabrata Chakraborti Pdf

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.

Author : Larry Wasserman
Publisher : Springer Science & Business Media
Page : 272 pages
File Size : 48,7 Mb
Release : 2006-09-10
Category : Mathematics
ISBN : 9780387306230

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All of Nonparametric Statistics by Larry Wasserman Pdf

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.

Author : Jean Dickinson Gibbons
Publisher : SAGE
Page : 108 pages
File Size : 44,5 Mb
Release : 1993-02-25
Category : Reference
ISBN : 0803946643

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Nonparametric Measures of Association by Jean Dickinson Gibbons Pdf

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.

Author : Jean Dickinson Gibbons,Subhabrata Chakraborti
Publisher : Chapman and Hall/CRC
Page : 650 pages
File Size : 50,5 Mb
Release : 2010-07-26
Category : Mathematics
ISBN : 1420077619

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Nonparametric Statistical Inference, Fifth Edition by Jean Dickinson Gibbons,Subhabrata Chakraborti Pdf

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.

Author : Jean Dickinson Gibbons,Subhabrata Chakraborti
Publisher : CRC Press
Page : 680 pages
File Size : 44,8 Mb
Release : 2003-05-09
Category : Mathematics
ISBN : 0824740521

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Nonparametric Statistical Inference, Fourth Edition by Jean Dickinson Gibbons,Subhabrata Chakraborti Pdf

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.

Author : Christopher Z. Mooney,Robert D. Duval,Robert Duvall
Publisher : SAGE
Page : 84 pages
File Size : 40,7 Mb
Release : 1993-08-09
Category : Philosophy
ISBN : 080395381X

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Bootstrapping by Christopher Z. Mooney,Robert D. Duval,Robert Duvall Pdf

"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.

Author : Sneh Gulati,William J. Padgett
Publisher : Springer Science & Business Media
Page : 123 pages
File Size : 52,9 Mb
Release : 2013-03-14
Category : Mathematics
ISBN : 9780387215495

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Parametric and Nonparametric Inference from Record-Breaking Data by Sneh Gulati,William J. Padgett Pdf

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.

Author : Anonim
Publisher : Unknown
Page : 338 pages
File Size : 47,5 Mb
Release : 1956
Category : Electronic
ISBN : 8210379456XXX

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Nonparametric Statistics by Anonim Pdf

Author : Madan Lal Puri
Publisher : Cambridge University Press
Page : 0 pages
File Size : 52,8 Mb
Release : 2009-01-08
Category : Mathematics
ISBN : 0521093058

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Nonparametric Techniques in Statistical Inference by Madan Lal Puri Pdf

Nonparametric techniques in statistics are those in which the data are ranked in order according to some particular characteristic. When applied to measurable characteristics, the use of such techniques often saves considerable calculation as compared with more formal methods, with only slight loss of accuracy. The field of nonparametric statistics is occupying an increasingly important role in statistical theory as well as in its applications. Nonparametric methods are mathematically elegant, and they also yield significantly improved performances in applications to agriculture, education, biometrics, medicine, communication, economics and industry.

Author : Thomas P. Hettmansperger,Joseph W. McKean
Publisher : John Wiley & Sons
Page : 492 pages
File Size : 47,6 Mb
Release : 1998
Category : Nonparametric statistics
ISBN : STANFORD:36105023161156

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Robust Nonparametric Statistical Methods by Thomas P. Hettmansperger,Joseph W. McKean Pdf

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.

Author : Chiara Brombin,Luigi Salmaso,Lara Fontanella,Luigi Ippoliti,Caterina Fusilli
Publisher : Springer
Page : 115 pages
File Size : 48,7 Mb
Release : 2016-02-19
Category : Mathematics
ISBN : 3319263102

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Parametric and Nonparametric Inference for Statistical Dynamic Shape Analysis with Applications by Chiara Brombin,Luigi Salmaso,Lara Fontanella,Luigi Ippoliti,Caterina Fusilli Pdf

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.

Author : Larry Wasserman
Publisher : Springer Science & Business Media
Page : 446 pages
File Size : 47,8 Mb
Release : 2013-12-11
Category : Mathematics
ISBN : 9780387217369

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All of Statistics by Larry Wasserman Pdf

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.

Author : Subhashis Ghosal,Aad van der Vaart
Publisher : Cambridge University Press
Page : 671 pages
File Size : 51,9 Mb
Release : 2017-06-26
Category : Business & Economics
ISBN : 9780521878265

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Fundamentals of Nonparametric Bayesian Inference by Subhashis Ghosal,Aad van der Vaart Pdf

Bayesian nonparametrics comes of age with this landmark text synthesizing theory, methodology and computation.