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Permutation Tests for Stochastic Ordering and ANOVA: Theory and Applications with R de Dario Basso

Permutation Tests for Stochastic Ordering and ANOVA: Theory and Applications with R: Lecture Notes in Statistics, cartea 194

Autor Dario Basso, Fortunato Pesarin, Luigi Salmaso, Aldo Solari
en Limba Engleză Paperback – 28 apr 2009
Permutation testing for multivariate stochastic ordering and ANOVA designs is a fundamental issue in many scientific fields such as medicine, biology, pharmaceutical studies, engineering, economics, psychology, and social sciences. This book presents new advanced methods and related R codes to perform complex multivariate analyses. The prerequisites are a standard course in statistics and some background in multivariate analysis and R software.
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Specificații

ISBN-13: 9780387859552
ISBN-10: 0387859551
Pagini: 217
Ilustrații: XIV, 218 p.
Dimensiuni: 155 x 235 x 12 mm
Greutate: 0.33 kg
Ediția:2009
Editura: Springer
Colecția Springer
Seria Lecture Notes in Statistics

Locul publicării:New York, NY, United States

Public țintă

Research

Cuprins

I Stochastic Ordering.- Ordinal Data.- Multivariate Ordinal Data.- Multivariate Continuous Data.- Permutation Tests.- II Nonparametric ANOVA.- Nonparametric One-Way ANOVA.- Synchronized Permutation Tests in Two-way ANOVA.- Permutation Tests for Unreplicated Factorial Designs.

Recenzii

From the reviews:
“…Contributions to the permutation test literature are useful and handy…This latest…, from the camp of established leaders in this field, is no exception…Overall, this is an excellent book that should be read… widely, instead of just by those researchers working with permutations methods… A serious book that would make an excellent contribution to the professional library of any serious statistician, whether or not this statistician has previously used permutation tests.” (Biometrics)
“Students in courses on permutation methods and theoretical or applied statisticians interested in permutation methods. … The text contains the necessary formulas and algorithms for those who want to study the theoretical foundation of the methods that are presented, but also examples … are useful for the more applied statistician. … The book could be used as a textbook for an advanced course in statistics covering these subjects or as a reference book for theoretical or applied statisticians interested in permutation tests.” (Andreas Rosenblad, International Statistical Review, Vol. 78 (3), 2010)

Textul de pe ultima copertă

Permutation testing for multivariate stochastic ordering and ANOVA designs is a fundamental issue in many scientific fields such as medicine, biology, pharmaceutical studies, engineering, economics, psychology, and social sciences. This book presents new advanced methods and related R codes to perform complex multivariate analyses. The prerequisites are a standard course in statistics and some background in multivariate analysis and R software.
Dario Basso is a Post Doctoral Fellow at the Department of Management and Engineering of University of Padova His main research interests include permutation tests and design of experiments.
Fortunato Pesarin is Full Professor of Statistics at the Department of Statistics of the University of Padova. His main research interests include nonparametric methods, bootstrap methods, and permutation tests. He has published a leading book on multivariate permutation tests based on nonparametric combination methodology.
Luigi Salmaso is Associate Professor of Statistics at the Department of Management and Engineering of the University of Padova. His main research interests include permutation methods, multiple tests, and design of experiments. He has published more than 70 papers on permutation methods and design of experiments in international peer-reviewed journals.
Aldo Solari is a Post Doctoral Fellow at the Department of Chemical Process Engineering of the University of Padova. His main research interest is resampling-based multiple testing methods.

Caracteristici

Easy to understand multivariate methods for testing for a trend and for complex experimental designs Availability of R functions for all multivariate testing problems Easy to understand treatment of ordinal and continuous data Includes supplementary material: sn.pub/extras