Subset Selection in Regression: 2nd Edition (Paperback) book cover

Subset Selection in Regression

2nd Edition

By Alan Miller

Chapman and Hall/CRC

256 pages

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Description

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.

  • Table of Contents

    Introduction. Least-Squares Computations. Finding Subsets which Fit Well. Hypothesis Testing. How Many Variables? Estimation after Model Selection. Bayesian Methods. Conclusions.

    About the Author

    Miller, Alan

    About the Series

    Chapman & Hall/CRC Monographs on Statistics and Applied Probability

    Learn more…

    Subject Categories

    BISAC Subject Codes/Headings:
    MAT029000
    MATHEMATICS / Probability & Statistics / General