Nonparametric Statistical Methods Using R by Joseph Mckean

Nonparametric Statistical Methods Using R by Joseph Mckean

Regular price
Checking stock...
Regular price
Checking stock...
Proud to be B-Corp

Our business meets the highest standards of verified social and environmental performance, public transparency and legal accountability to balance profit and purpose. In short, we care about people and the planet.

The feel-good place to buy books
  • Free delivery in the UK
  • Supporting authors with AuthorSHARE
  • 100% recyclable packaging
  • B Corp - kinder to people and planet
  • Buy-back with World of Books - Sell Your Books

Nonparametric Statistical Methods Using R by Joseph Mckean

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.

"In general, this textbook is a good addition to the sparse offerings in entry-level nonparametricsThis book would be especially good for the shelf of anyone who already knows nonparametrics, but wants a reference for how to apply those techniques in R. As R becomes more ubiquitous and data science grows into its own, I think this approach will become more common and this book will be shown to be ahead of its time." (The American Statistician)

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.

SKU Nicht verfügbar
ISBN 13 9781439873434
ISBN 10 1439873437
Titel Nonparametric Statistical Methods Using R
Autor Joseph Mckean
Serie Chapman And Hall Crc Texts In Statistical Science
Buchzustand Nicht verfügbar
Bindungsart Hardback
Verlag Taylor & Francis Inc
Erscheinungsjahr 2014-10-15
Seitenanzahl 288
Hinweis auf dem Einband Die Abbildung des Buches dient nur Illustrationszwecken, die tatsächliche Bindung, das Cover und die Auflage können sich davon unterscheiden.
Hinweis Nicht verfügbar