Nonparametric Methods In Statistics

Download Nonparametric Methods In Statistics full books in PDF, epub, and Kindle. Read online Nonparametric Methods In Statistics ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!

Nonparametric Statistical Methods

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

DOWNLOAD NOW!

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.

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)

DOWNLOAD NOW!

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 Methods Using R

Author : John Kloke
Publisher : CRC Press
ISBN 13 : 1439873445
Total Pages : 283 pages
Book Rating : 4.4/5 (398 download)

DOWNLOAD NOW!

Book Synopsis Nonparametric Statistical Methods Using R by : John Kloke

Download or read book Nonparametric Statistical Methods Using R written by John Kloke and published by CRC Press. This book was released on 2014-10-09 with total page 283 pages. Available in PDF, EPUB and Kindle. Book excerpt: A Practical Guide to Implementing Nonparametric and Rank-Based Procedures Nonparametric Statistical Methods Using R covers traditional nonparametric methods and rank-based analyses, including estimation and inference for models ranging from simple location models to general linear and nonlinear models for uncorrelated and correlated responses. The authors emphasize applications and statistical computation. They illustrate the methods with many real and simulated data examples using R, including the packages Rfit and npsm. The book first gives an overview of the R language and basic statistical concepts before discussing nonparametrics. It presents rank-based methods for one- and two-sample problems, procedures for regression models, computation for general fixed-effects ANOVA and ANCOVA models, and time-to-event analyses. The last two chapters cover more advanced material, including high breakdown fits for general regression models and rank-based inference for cluster correlated data. The book can be used as a primary text or supplement in a course on applied nonparametric or robust procedures and as a reference for researchers who need to implement nonparametric and rank-based methods in practice. Through numerous examples, it shows readers how to apply these methods using R.

Robust Nonparametric Statistical Methods

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

DOWNLOAD NOW!

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.

Nonparametric Methods in Statistics with SAS Applications

Author : Olga Korosteleva
Publisher : CRC Press
ISBN 13 : 1466580631
Total Pages : 193 pages
Book Rating : 4.4/5 (665 download)

DOWNLOAD NOW!

Book Synopsis Nonparametric Methods in Statistics with SAS Applications by : Olga Korosteleva

Download or read book Nonparametric Methods in Statistics with SAS Applications written by Olga Korosteleva and published by CRC Press. This book was released on 2013-08-19 with total page 193 pages. Available in PDF, EPUB and Kindle. Book excerpt: Designed for a graduate course in applied statistics, Nonparametric Methods in Statistics with SAS Applications teaches students how to apply nonparametric techniques to statistical data. It starts with the tests of hypotheses and moves on to regression modeling, time-to-event analysis, density estimation, and resampling methods.The text begins wit

Nonparametric Statistical Methods For Complete and Censored Data

Author : M.M. Desu
Publisher : CRC Press
ISBN 13 : 9781584883197
Total Pages : 392 pages
Book Rating : 4.8/5 (831 download)

DOWNLOAD NOW!

Book Synopsis Nonparametric Statistical Methods For Complete and Censored Data by : M.M. Desu

Download or read book Nonparametric Statistical Methods For Complete and Censored Data written by M.M. Desu and published by CRC Press. This book was released on 2003-09-29 with total page 392 pages. Available in PDF, EPUB and Kindle. Book excerpt: Balancing the "cookbook" approach of some texts with the more mathematical approach of others, Nonparametric Statistical Methods for Complete and Censored Data introduces commonly used non-parametric methods for complete data and extends those methods to right censored data analysis. Whenever possible, the authors derive their methodology from the general theory of statistical inference and introduce the concepts intuitively for students with minimal backgrounds. Derivations and mathematical details are relegated to appendices at the end of each chapter, which allows students to easily proceed through each chapter without becoming bogged down in a lot of mathematics. In addition to the nonparametric methods for analyzing complete and censored data, the book covers optimal linear rank statistics, clinical equivalence, analysis of block designs, and precedence tests. To make the material more accessible and practical, the authors use SAS programs to illustrate the various methods included. Exercises in each chapter, SAS code, and a clear, accessible presentation make this an outstanding text for a one-semester senior or graduate-level course in nonparametric statistics for students in a variety of disciplines, from statistics and biostatistics to business, psychology, and the social scientists. Prerequisites: Students will need a solid background in calculus and a two-semester course in mathematical statistics.

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)

DOWNLOAD NOW!

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.

Practical Nonparametric Statistics

Author : W. J. Conover
Publisher :
ISBN 13 :
Total Pages : 506 pages
Book Rating : 4.:/5 (319 download)

DOWNLOAD NOW!

Book Synopsis Practical Nonparametric Statistics by : W. J. Conover

Download or read book Practical Nonparametric Statistics written by W. J. Conover and published by . This book was released on 1980-09-17 with total page 506 pages. Available in PDF, EPUB and Kindle. Book excerpt: Probability theory; Statistical inference; Some tests based on the binomial distribution; Contingency tables; Some methods based on ranks; Statistics of the koolmogorov-smirnov type.

Nonparametric Statistics

Author : Gregory W. Corder
Publisher : John Wiley & Sons
ISBN 13 : 1118840429
Total Pages : 288 pages
Book Rating : 4.1/5 (188 download)

DOWNLOAD NOW!

Book Synopsis Nonparametric Statistics by : Gregory W. Corder

Download or read book Nonparametric Statistics written by Gregory W. Corder and published by John Wiley & Sons. This book was released on 2014-04-14 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt: “...a very useful resource for courses in nonparametric statistics in which the emphasis is on applications rather than on theory. It also deserves a place in libraries of all institutions where introductory statistics courses are taught." –CHOICE This Second Edition presents a practical and understandable approach that enhances and expands the statistical toolset for readers. This book includes: New coverage of the sign test and the Kolmogorov-Smirnov two-sample test in an effort to offer a logical and natural progression to statistical power SPSS® (Version 21) software and updated screen captures to demonstrate how to perform and recognize the steps in the various procedures Data sets and odd-numbered solutions provided in an appendix, and tables of critical values Supplementary material to aid in reader comprehension, which includes: narrated videos and screen animations with step-by-step instructions on how to follow the tests using SPSS; online decision trees to help users determine the needed type of statistical test; and additional solutions not found within the book.

Nonparametric Statistics for Non-Statisticians

Author : Gregory W. Corder
Publisher : John Wiley & Sons
ISBN 13 : 1118211251
Total Pages : 199 pages
Book Rating : 4.1/5 (182 download)

DOWNLOAD NOW!

Book Synopsis Nonparametric Statistics for Non-Statisticians by : Gregory W. Corder

Download or read book Nonparametric Statistics for Non-Statisticians written by Gregory W. Corder and published by John Wiley & Sons. This book was released on 2011-09-20 with total page 199 pages. Available in PDF, EPUB and Kindle. Book excerpt: A practical and understandable approach to nonparametric statistics for researchers across diverse areas of study As the importance of nonparametric methods in modern statistics continues to grow, these techniques are being increasingly applied to experimental designs across various fields of study. However, researchers are not always properly equipped with the knowledge to correctly apply these methods. Nonparametric Statistics for Non-Statisticians: A Step-by-Step Approach fills a void in the current literature by addressing nonparametric statistics in a manner that is easily accessible for readers with a background in the social, behavioral, biological, and physical sciences. Each chapter follows the same comprehensive format, beginning with a general introduction to the particular topic and a list of main learning objectives. A nonparametric procedure is then presented and accompanied by context-based examples that are outlined in a step-by-step fashion. Next, SPSS® screen captures are used to demonstrate how to perform and recognize the steps in the various procedures. Finally, the authors identify and briefly describe actual examples of corresponding nonparametric tests from diverse fields. Using this organized structure, the book outlines essential skills for the application of nonparametric statistical methods, including how to: Test data for normality and randomness Use the Wilcoxon signed rank test to compare two related samples Apply the Mann-Whitney U test to compare two unrelated samples Compare more than two related samples using the Friedman test Employ the Kruskal-Wallis H test to compare more than two unrelated samples Compare variables of ordinal or dichotomous scales Test for nominal scale data A detailed appendix provides guidance on inputting and analyzing the presented data using SPSS®, and supplemental tables of critical values are provided. In addition, the book's FTP site houses supplemental data sets and solutions for further practice. Extensively classroom tested, Nonparametric Statistics for Non-Statisticians is an ideal book for courses on nonparametric statistics at the upper-undergraduate and graduate levels. It is also an excellent reference for professionals and researchers in the social, behavioral, and health sciences who seek a review of nonparametric methods and relevant applications.

A Distribution-Free Theory of Nonparametric Regression

Author : László Györfi
Publisher : Springer Science & Business Media
ISBN 13 : 0387224424
Total Pages : 662 pages
Book Rating : 4.3/5 (872 download)

DOWNLOAD NOW!

Book Synopsis A Distribution-Free Theory of Nonparametric Regression by : László Györfi

Download or read book A Distribution-Free Theory of Nonparametric Regression written by László Györfi and published by Springer Science & Business Media. This book was released on 2006-04-18 with total page 662 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a systematic in-depth analysis of nonparametric regression with random design. It covers almost all known estimates. The emphasis is on distribution-free properties of the estimates.

An Introduction to Nonparametric Statistics

Author : John E. Kolassa
Publisher : CRC Press
ISBN 13 : 0429511361
Total Pages : 225 pages
Book Rating : 4.4/5 (295 download)

DOWNLOAD NOW!

Book Synopsis An Introduction to Nonparametric Statistics by : John E. Kolassa

Download or read book An Introduction to Nonparametric Statistics written by John E. Kolassa and published by CRC Press. This book was released on 2020-09-28 with total page 225 pages. Available in PDF, EPUB and Kindle. Book excerpt: An Introduction to Nonparametric Statistics presents techniques for statistical analysis in the absence of strong assumptions about the distributions generating the data. Rank-based and resampling techniques are heavily represented, but robust techniques are considered as well. These techniques include one-sample testing and estimation, multi-sample testing and estimation, and regression. Attention is paid to the intellectual development of the field, with a thorough review of bibliographical references. Computational tools, in R and SAS, are developed and illustrated via examples. Exercises designed to reinforce examples are included. Features Rank-based techniques including sign, Kruskal-Wallis, Friedman, Mann-Whitney and Wilcoxon tests are presented Tests are inverted to produce estimates and confidence intervals Multivariate tests are explored Techniques reflecting the dependence of a response variable on explanatory variables are presented Density estimation is explored The bootstrap and jackknife are discussed This text is intended for a graduate student in applied statistics. The course is best taken after an introductory course in statistical methodology, elementary probability, and regression. Mathematical prerequisites include calculus through multivariate differentiation and integration, and, ideally, a course in matrix algebra.

Nonparametric Density Estimation

Author : Luc Devroye
Publisher : New York ; Toronto : Wiley
ISBN 13 :
Total Pages : 376 pages
Book Rating : 4.:/5 (319 download)

DOWNLOAD NOW!

Book Synopsis Nonparametric Density Estimation by : Luc Devroye

Download or read book Nonparametric Density Estimation written by Luc Devroye and published by New York ; Toronto : Wiley. This book was released on 1985-01-18 with total page 376 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gives a rigorous, systematic treatment of density estimates, their construction, use and analysis with full proofs. It develops L1 theory, rather than the classical L2, showing how L1 exposes fundamental properties of density estimates masked by L2.

Applied Nonparametric Statistical Methods

Author : Peter Sprent
Publisher : Springer Science & Business Media
ISBN 13 : 9400912234
Total Pages : 268 pages
Book Rating : 4.4/5 (9 download)

DOWNLOAD NOW!

Book Synopsis Applied Nonparametric Statistical Methods by : Peter Sprent

Download or read book Applied Nonparametric Statistical Methods written by Peter Sprent and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 268 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a practical introduction to statistical techniques called nonpara metric methods. Using examples, we explain assumptions and demonstrate procedures; theory is kept to a minimum. We show how basic problems are tackled and try to clear up common misapprehensions so as to help both students of statistics meeting the methods for the first time and workers in other fields faced with data needing simple but informative analysis. An analogy between experimenters and car drivers describes our aim. Statistical analyses may be done by following a set of rules without understanding their logical basis, but this has dangers. It is like driving a car with no inkling ofhow the internal combustion engine, the gears, the ignition system, the brakes actually work. Understanding the rudiments helps one get better performance and makesdrivingsafer;appropriate gearchanges become a way to reduce engine stress, prolong engine life, improve fuel economy, minimize wear on brake linings. Knowing how to change the engine oil or replace worn sparking plugs is notessential for adriver, but it will reduce costs. Learning such basics will not make one a fully fledged mechanic, even less an automotive engineer; but it all contributes to more economical and safer driving, alertingone to the dangers ofbald tyres, aleakingexhaust, worn brake linings.

A Parametric Approach to Nonparametric Statistics

Author : Mayer Alvo
Publisher : Springer
ISBN 13 : 3319941534
Total Pages : 279 pages
Book Rating : 4.3/5 (199 download)

DOWNLOAD NOW!

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 279 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.

Combinatorial Methods in Density Estimation

Author : Luc Devroye
Publisher : Springer Science & Business Media
ISBN 13 : 1461301254
Total Pages : 219 pages
Book Rating : 4.4/5 (613 download)

DOWNLOAD NOW!

Book Synopsis Combinatorial Methods in Density Estimation by : Luc Devroye

Download or read book Combinatorial Methods in Density Estimation written by Luc Devroye and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 219 pages. Available in PDF, EPUB and Kindle. Book excerpt: Density estimation has evolved enormously since the days of bar plots and histograms, but researchers and users are still struggling with the problem of the selection of the bin widths. This book is the first to explore a new paradigm for the data-based or automatic selection of the free parameters of density estimates in general so that the expected error is within a given constant multiple of the best possible error. The paradigm can be used in nearly all density estimates and for most model selection problems, both parametric and nonparametric.

Nonparametric Methods

Author : P. R. Krishnaiah
Publisher : Elsevier Health Sciences
ISBN 13 :
Total Pages : 1016 pages
Book Rating : 4.:/5 (319 download)

DOWNLOAD NOW!

Book Synopsis Nonparametric Methods by : P. R. Krishnaiah

Download or read book Nonparametric Methods written by P. R. Krishnaiah and published by Elsevier Health Sciences. This book was released on 1984 with total page 1016 pages. Available in PDF, EPUB and Kindle. Book excerpt: Classical developments. Linear models. Order statistics and empitical distribution. Estimation procedures. Stochastic aproximation and density estimation. Life testing and reliability. Miscellaneous topics. Applications. Tables.