Robust Nonparametric Statistical Methods (Hardcover, 2nd edition)

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

General

Imprint:	Crc Press
Country of origin:	United States
Series:	Chapman & Hall/CRC Monographs on Statistics and Applied Probability
Release date:	December 2010
First published:	2011
Authors:	Thomas P. Hettmansperger • Joseph W. McKean
Dimensions:	254 x 178 x 35mm (L x W x T)
Format:	Hardcover
Pages:	554
Edition:	2nd edition
ISBN-13:	978-1-4398-0908-2
Categories:	Books > Science & Mathematics > Mathematics > Probability & statistics
LSN:	1-4398-0908-9
Barcode:	9781439809082

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