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Nonparametric Statistical Methods Using R (Chapman & Hall/CRC Texts in Statistical Science) - Hardcover
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This book 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, which are available on CRAN. Each chapter includes exercises, making the book suitable for an undergraduate or graduate course.
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Über die Autorin bzw. den Autor
John Kloke is a biostatistician and assistant scientist at the University of Wisconsin–Madison. He has held faculty positions at the University of Pittsburgh, Bucknell University, and Pomona College. An R user for more than 15 years, he is an author and maintainer of numerous R packages, including Rfit and npsm. He has published papers on nonparametric rank-based estimation, including analysis of cluster correlated data.
Joseph W. McKean is a professor of statistics at Western Michigan University. He has published many papers on nonparametric and robust statistical procedures and has co-authored several books, including Robust Nonparametric Statistical Methods and Introduction to Mathematical Statistics. He is an associate editor of several statistics journals and a fellow of the American Statistical Association.
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Nonparametric Statistical Methods Using R
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Nonparametric Statistical Methods Using R (Chapman & Hall/CRC Texts in Statistical Science)
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Nanparametric Statistical Methods Using R
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