9780367739720-0367739720-Nonparametric Statistical Methods Using R (Chapman & Hall/CRC Texts in Statistical Science)

Nonparametric Statistical Methods Using R (Chapman & Hall/CRC Texts in Statistical Science)

ISBN-13: 9780367739720
ISBN-10: 0367739720
Edition: 1
Author: John Kloke, Joseph McKean
Publication date: 2020
Publisher: Routledge
Format: Paperback 288 pages
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Book details

ISBN-13: 9780367739720
ISBN-10: 0367739720
Edition: 1
Author: John Kloke, Joseph McKean
Publication date: 2020
Publisher: Routledge
Format: Paperback 288 pages

Summary

Nonparametric Statistical Methods Using R (Chapman & Hall/CRC Texts in Statistical Science) (ISBN-13: 9780367739720 and ISBN-10: 0367739720), written by authors John Kloke, Joseph McKean, was published by Routledge in 2020. With an overall rating of 4.5 stars, it's a notable title among other Applied (Mathematics) books. You can easily purchase or rent Nonparametric Statistical Methods Using R (Chapman & Hall/CRC Texts in Statistical Science) (Paperback) from BooksRun, along with many other new and used Applied books and textbooks. And, if you're looking to sell your copy, our current buyback offer is $1.59.

Description

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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