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  • Broschiertes Buch

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.

Produktbeschreibung
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.
Rezensionen
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)