Subset Selection in Regression (Paperback, 2nd edition)

Originally published in 1990, the first edition of Subset Selection in Regression filled a significant gap in the literature, and its critical and popular success has continued for more than a decade. Thoroughly revised to reflect progress in theory, methods, and computing power, the second edition promises to continue that tradition. The author has thoroughly updated each chapter, incorporated new material on recent developments, and included more examples and references. New in the Second Edition: A separate chapter on Bayesian methods Complete revision of the chapter on estimation A major example from the field of near infrared spectroscopy More emphasis on cross-validation Greater focus on bootstrapping Stochastic algorithms for finding good subsets from large numbers of predictors when an exhaustive search is not feasible Software available on the Internet for implementing many of the algorithms presented More examples Subset Selection in Regression, Second Edition remains dedicated to the techniques for fitting and choosing models that are linear in their parameters and to understanding and correcting the bias introduced by selecting a model that fits only slightly better than others. The presentation is clear, concise, and belongs on the shelf of anyone researching, using, or teaching subset selecting techniques.

General

Imprint:	Crc Press
Country of origin:	United Kingdom
Series:	Chapman & Hall/CRC Monographs on Statistics and Applied Probability
Release date:	September 2019
First published:	2002
Authors:	Alan Miller
Dimensions:	229 x 152 x 25mm (L x W x T)
Format:	Paperback
Pages:	256
Edition:	2nd edition
ISBN-13:	978-0-367-39622-0
Categories:	Books > Science & Mathematics > Mathematics > Probability & statistics Books > Computing & IT > General theory of computing > General Books > Computing & IT > Applications of computing > General
LSN:	0-367-39622-X
Barcode:	9780367396220

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