Robust Nonparametric Statistical Methods (Chapman & Hall/CRC Monographs on Statistics and Applied Probability) - Hardcover

Hettmansperger, Thomas P.; McKean, Joseph W.

Hardcover

ISBN 10: 1439809089 ISBN 13: 9781439809082

Publisher: CRC Press, 2010

Synopsis

Presenting an extensive set of tools and methods for data analysis, Robust Nonparametric Statistical Methods, Second Edition covers univariate tests and estimates with extensions to linear models, multivariate models, times series models, experimental designs, and mixed models. It follows the approach of the first edition by developing rank-based methods from the unifying theme of geometry. This edition, however, includes more models and methods and significantly extends the possible analyses based on ranks.

New to the Second Edition

• A new section on rank procedures for nonlinear models
• A new chapter on models with dependent error structure, covering rank methods for mixed models, general estimating equations, and time series
• New material on the development of computationally efficient affine invariant/equivariant sign methods based on transform-retransform techniques in multivariate models

Taking a comprehensive, unified approach to statistical analysis, the book continues to describe one- and two-sample problems, the basic development of rank methods in the linear model, and fixed effects experimental designs. It also explores models with dependent error structure and multivariate models. The authors illustrate the implementation of the methods using many real-world examples and R. More information about the data sets and R packages can be found at www.crcpress.com

About this title

From the Publisher

An alternative to the least squares approach, based on ranks of the data. This book discusses one- and two-sample location models, linear models (including multiple regression and designed experiments), and multivariate models. It develops rank test and estimates for all models, including bounded influence and high breakdown methods. It emphasizes efficiency and robustness and illustrates all methods on data sets.

About the Author

Thomas P. Hettmansperger is a professor emeritus of statistics at Penn State University. Dr. Hettmansperger is a fellow of the American Statistical Association and Institute of Mathematical Statistics and an elected member of the International Statistical Institute. His research interests span nonparametric statistics, robust methods, and mixture models.

Joseph W. McKean is a professor of statistics at Western Michigan University. His research interests include robust nonparametric procedures for linear, nonlinear, and mixed models and times series designs. A fellow of the American Statistical Association, Dr. McKean has developed highly efficient and high breakdown procedures.

Edition details

• Publisher: CRC Press
• Publication date: 2010
• ISBN 10: 1439809089
• ISBN 13: 9781439809082
• Binding: Hardcover
• Language: English
• Edition number: 2
• Number of pages: 554