Nonparametric Statistical Methods Using R

Autorentext

John D. Kloke is a bit of a jack-of-all-trades as he has worked as a clinical trial statistician supporting industry as well as academic studies and he also served as a teacher-scholar at several academic institutions. He has held faculty positions at the University of California - Santa Barbara, University of Wisconsin - Madison, University of Pittsburgh, Bucknell University, and Pomona College. An early adopter of R, 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 emeritus 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 co-edited the book Robust Rank-Based and Nonparametric Methods. He served as an associate editor of several statistics journals and is a fellow of the American Statistical Association.

Klappentext

This thoroughly updated and expanded second edition covers traditional nonparametric methods and rank-based analyses. Two new chapters covering multivariate analyses and big data have been added. Core classical nonparametrics chapters on one- and two-sample problems have been expanded

Inhalt

1. Introduction 2. One-Sample Problems 3. Two-Sample Problems 4. Regression 5. ANOVA-Type Rank-Based Procedures 6. Categorical 7. Linear Models 8. Topics in Regression 9. Cluster Correlated Data 10. Multivariate Analysis 11. Big Data Appendix - R Version Information