Robust nonparametric statistical methods
Author(s)
Bibliographic Information
Robust nonparametric statistical methods
（Monographs on statistics and applied probability, 119）
CRC Press, c2011
2nd ed
- : hbk
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Note
Includes bibliographical references (p. 495-520) and indexes
Description and Table of Contents
Description
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
Table of Contents
One-Sample Problems. Two-Sample Problems. Linear Models. Experimental Designs: Fixed Effects. Models with Dependent Error Structure. Multivariate. Appendix. References. Index.
by "Nielsen BookData"
