Nonparametric Methods in Multivariate Analysis

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Publisher :
ISBN 13 :
Total Pages : 464 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis Nonparametric Methods in Multivariate Analysis by : Madan Lal Puri

Download or read book Nonparametric Methods in Multivariate Analysis written by Madan Lal Puri and published by . This book was released on 1971 with total page 464 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Multivariate Nonparametric Methods with R

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Publisher : Springer Science & Business Media
ISBN 13 : 1441904689
Total Pages : 239 pages
Book Rating : 4.4/5 (419 download)

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Book Synopsis Multivariate Nonparametric Methods with R by : Hannu Oja

Download or read book Multivariate Nonparametric Methods with R written by Hannu Oja and published by Springer Science & Business Media. This book was released on 2010-03-25 with total page 239 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers a new, fairly efficient, and robust alternative to analyzing multivariate data. The analysis of data based on multivariate spatial signs and ranks proceeds very much as does a traditional multivariate analysis relying on the assumption of multivariate normality; the regular L2 norm is just replaced by different L1 norms, observation vectors are replaced by spatial signs and ranks, and so on. A unified methodology starting with the simple one-sample multivariate location problem and proceeding to the general multivariate multiple linear regression case is presented. Companion estimates and tests for scatter matrices are considered as well. The R package MNM is available for computation of the procedures. This monograph provides an up-to-date overview of the theory of multivariate nonparametric methods based on spatial signs and ranks. The classical book by Puri and Sen (1971) uses marginal signs and ranks and different type of L1 norm. The book may serve as a textbook and a general reference for the latest developments in the area. Readers are assumed to have a good knowledge of basic statistical theory as well as matrix theory. Hannu Oja is an academy professor and a professor in biometry in the University of Tampere. He has authored and coauthored numerous research articles in multivariate nonparametrical and robust methods as well as in biostatistics.

Nonparametric Methods in Multivariate Analysis

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ISBN 13 :
Total Pages : 440 pages
Book Rating : 4.:/5 (853 download)

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Book Synopsis Nonparametric Methods in Multivariate Analysis by : P.K. Sen

Download or read book Nonparametric Methods in Multivariate Analysis written by P.K. Sen and published by . This book was released on 1941 with total page 440 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Multivariate Nonparametric Methods with R

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Publisher : Springer
ISBN 13 : 9781441904690
Total Pages : 234 pages
Book Rating : 4.9/5 (46 download)

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Book Synopsis Multivariate Nonparametric Methods with R by : Hannu Oja

Download or read book Multivariate Nonparametric Methods with R written by Hannu Oja and published by Springer. This book was released on 2010-11-11 with total page 234 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Nonparametric Methods for Multivariate Analysis Using Statistically Equivalent Blocks

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ISBN 13 :
Total Pages : 28 pages
Book Rating : 4.:/5 (227 download)

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Book Synopsis Nonparametric Methods for Multivariate Analysis Using Statistically Equivalent Blocks by :

Download or read book Nonparametric Methods for Multivariate Analysis Using Statistically Equivalent Blocks written by and published by . This book was released on 1996 with total page 28 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multivariate statistical procedures developed under normality assumptions are well advanced. Some of these procedures claim robustness properties, especially in a large sample situation, that may serve to broaden their range of application. Nonparametric methods for multivariate analysis have been pursued, but their more complete development awaits further research. This report considers nonparametric multivariate hypothesis testing in both one- and two-sample situations. Comparable univariate procedures do not extend readily to higher dimensions. The methods considered are based on the properties of statistically equivalent blocks. A new approach using a proximity-based cutting function for block construction is described. Statistically equivalent blocks, while holding the promise of important practical application, has received limited research attention.

Modern Nonparametric, Robust and Multivariate Methods

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Publisher : Springer
ISBN 13 : 3319224042
Total Pages : 513 pages
Book Rating : 4.3/5 (192 download)

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Book Synopsis Modern Nonparametric, Robust and Multivariate Methods by : Klaus Nordhausen

Download or read book Modern Nonparametric, Robust and Multivariate Methods written by Klaus Nordhausen and published by Springer. This book was released on 2015-10-05 with total page 513 pages. Available in PDF, EPUB and Kindle. Book excerpt: Written by leading experts in the field, this edited volume brings together the latest findings in the area of nonparametric, robust and multivariate statistical methods. The individual contributions cover a wide variety of topics ranging from univariate nonparametric methods to robust methods for complex data structures. Some examples from statistical signal processing are also given. The volume is dedicated to Hannu Oja on the occasion of his 65th birthday and is intended for researchers as well as PhD students with a good knowledge of statistics.

Nonparametric Statistics: Theory And Methods

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Publisher : World Scientific
ISBN 13 : 981466359X
Total Pages : 279 pages
Book Rating : 4.8/5 (146 download)

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Book Synopsis Nonparametric Statistics: Theory And Methods by : Jayant V Deshpande

Download or read book Nonparametric Statistics: Theory And Methods written by Jayant V Deshpande and published by World Scientific. This book was released on 2017-10-17 with total page 279 pages. Available in PDF, EPUB and Kindle. Book excerpt: The number of books on Nonparametric Methodology is quite small as compared to, say, on Design of Experiments, Regression Analysis, Multivariate Analysis, etc. Because of being perceived as less effective, nonparametric methods are still the second choice. Actually, it has been demonstrated time and again that they are useful. We feel that there is still need for proper texts/applications/reference books on Nonparametric Methodology.This book will introduce various types of data encountered in practice and suggest the appropriate nonparametric methods, discuss their properties through null and non-null distributions whenever possible and demonstrate the very minor loss in power and efficiency in the nonparametric method, if any.The book will cover almost all topics of current interest such as bootstrapping, ranked set sampling, techniques for censored data and Bayesian analysis under nonparametric set ups.

Nonparametric Statistical Methods Using R

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Publisher : CRC Press
ISBN 13 : 1040025153
Total Pages : 466 pages
Book Rating : 4.0/5 (4 download)

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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 2024-05-20 with total page 466 pages. Available in PDF, EPUB and Kindle. Book excerpt: Praise for the first edition: “This book would be especially good for the shelf of anyone who already knows nonparametrics, but wants a reference for how to apply those techniques in R.” -The American Statistician This thoroughly updated and expanded second edition of Nonparametric Statistical Methods Using R covers traditional nonparametric methods and rank-based analyses. Two new chapters covering multivariate analyses and big data have been added. Core classical nonparametrics chapters on one- and two-sample problems have been expanded to include discussions on ties as well as power and sample size determination. Common machine learning topics --- including k-nearest neighbors and trees --- have also been included in this new edition. Key Features: Covers a wide range of models including location, linear regression, ANOVA-type, mixed models for cluster correlated data, nonlinear, and GEE-type. Includes robust methods for linear model analyses, big data, time-to-event analyses, timeseries, and multivariate. Numerous examples illustrate the methods and their computation. R packages are available for computation and datasets. Contains two completely new chapters on big data and multivariate analysis. The book is suitable for advanced undergraduate and graduate students in statistics and data science, and students of other majors with a solid background in statistical methods including regression and ANOVA. It will also be of use to researchers working with nonparametric and rank-based methods in practice.

Nonparametric Methods in Multivariate Analysis

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Publisher :
ISBN 13 :
Total Pages : 472 pages
Book Rating : 4.:/5 (44 download)

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Book Synopsis Nonparametric Methods in Multivariate Analysis by : Madan Lal Puri

Download or read book Nonparametric Methods in Multivariate Analysis written by Madan Lal Puri and published by . This book was released on 1971-01-15 with total page 472 pages. Available in PDF, EPUB and Kindle. Book excerpt: A brief outline of the material covered in the book. Preliminaries. A survey of nonparametric inference. Rank tests for the multivariate single-sample location problems. Multivariate multisample rank tests for location and scale. Estimators in linear models (one way layouts) based on rank tests. Rank procedures in factorial experiments. Rank tests for independence. Rank tests for homogeneity of dispersion matrices.

Multivariate Statistical Methods

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Publisher : CRC Press
ISBN 13 : 1498728995
Total Pages : 227 pages
Book Rating : 4.4/5 (987 download)

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Book Synopsis Multivariate Statistical Methods by : Bryan F.J. Manly

Download or read book Multivariate Statistical Methods written by Bryan F.J. Manly and published by CRC Press. This book was released on 2016-11-03 with total page 227 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multivariate Statistical Methods: A Primer provides an introductory overview of multivariate methods without getting too deep into the mathematical details. This fourth edition is a revised and updated version of this bestselling introductory textbook. It retains the clear and concise style of the previous editions of the book and focuses on examples from biological and environmental sciences. The major update with this edition is that R code has been included for each of the analyses described, although in practice any standard statistical package can be used. The original idea with this book still applies. This was to make it as short as possible and enable readers to begin using multivariate methods in an intelligent manner. With updated information on multivariate analyses, new references, and R code included, this book continues to provide a timely introduction to useful tools for multivariate statistical analysis.

Nonparametric Methods for Multivariate Data and Regression Analysis

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ISBN 13 :
Total Pages : 272 pages
Book Rating : 4.:/5 (59 download)

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Book Synopsis Nonparametric Methods for Multivariate Data and Regression Analysis by : Xin Yan

Download or read book Nonparametric Methods for Multivariate Data and Regression Analysis written by Xin Yan and published by . This book was released on 1998 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Methods of Multivariate Analysis

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Publisher : John Wiley & Sons
ISBN 13 : 0471461725
Total Pages : 739 pages
Book Rating : 4.4/5 (714 download)

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Book Synopsis Methods of Multivariate Analysis by : Alvin C. Rencher

Download or read book Methods of Multivariate Analysis written by Alvin C. Rencher and published by John Wiley & Sons. This book was released on 2003-04-14 with total page 739 pages. Available in PDF, EPUB and Kindle. Book excerpt: Amstat News asked three review editors to rate their top five favorite books in the September 2003 issue. Methods of Multivariate Analysis was among those chosen. When measuring several variables on a complex experimental unit, it is often necessary to analyze the variables simultaneously, rather than isolate them and consider them individually. Multivariate analysis enables researchers to explore the joint performance of such variables and to determine the effect of each variable in the presence of the others. The Second Edition of Alvin Rencher's Methods of Multivariate Analysis provides students of all statistical backgrounds with both the fundamental and more sophisticated skills necessary to master the discipline. To illustrate multivariate applications, the author provides examples and exercises based on fifty-nine real data sets from a wide variety of scientific fields. Rencher takes a "methods" approach to his subject, with an emphasis on how students and practitioners can employ multivariate analysis in real-life situations. The Second Edition contains revised and updated chapters from the critically acclaimed First Edition as well as brand-new chapters on: Cluster analysis Multidimensional scaling Correspondence analysis Biplots Each chapter contains exercises, with corresponding answers and hints in the appendix, providing students the opportunity to test and extend their understanding of the subject. Methods of Multivariate Analysis provides an authoritative reference for statistics students as well as for practicing scientists and clinicians.

Robust Nonparametric Statistical Methods

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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.

An Introduction to Nonparametric Statistics

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

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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.

The Use of Nonparametric Methods of Multivariate Analysis to Evaluate Adaptive Behaviors in the Retarded

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Publisher :
ISBN 13 :
Total Pages : 34 pages
Book Rating : 4.:/5 (86 download)

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Book Synopsis The Use of Nonparametric Methods of Multivariate Analysis to Evaluate Adaptive Behaviors in the Retarded by : Ellen M. Naor

Download or read book The Use of Nonparametric Methods of Multivariate Analysis to Evaluate Adaptive Behaviors in the Retarded written by Ellen M. Naor and published by . This book was released on 1975 with total page 34 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Nonparametric Statistics and Mixture Models

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Publisher : World Scientific
ISBN 13 : 9814340553
Total Pages : 370 pages
Book Rating : 4.8/5 (143 download)

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Book Synopsis Nonparametric Statistics and Mixture Models by : David R. Hunter

Download or read book Nonparametric Statistics and Mixture Models written by David R. Hunter and published by World Scientific. This book was released on 2011 with total page 370 pages. Available in PDF, EPUB and Kindle. Book excerpt: This festschrift includes papers authored by many collaborators, colleagues, and students of Professor Thomas P Hettmansperger, who worked in research in nonparametric statistics, rank statistics, robustness, and mixture models during a career that spanned nearly 40 years. It is a broad sample of peer-reviewed, cutting-edge research related to nonparametrics and mixture models.

Nonparametric Methods

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

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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.