北美最流行

非参数统计方法与R的运用

Nonparametric Statistical Methods Using R by John Kloke and Joseph W. McKean
English | 2014 | ISBN: 1439873437 | 287 pages | PDF | 2 MB
【作者简介】
John Kloke为美国University of Wisconsin（Madison）教授；Joseph W. McKean为美国Western Michigan University教授。

【教材简介】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.
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