Model selection and multimodel inference : a practical information-theoretic approach (Book, 2002) [WorldCat.org]
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Model selection and multimodel inference : a practical information-theoretic approach

Author: Kenneth P Burnham; David Raymond Anderson
Publisher: New York : Springer, ©2002.
Edition/Format:   Print book : English : 2nd edView all editions and formats
Summary:
This book is unique in that it covers the philosophy of model-based data analysis and a strategy for the analysis of empirical data. The book introduces information theoretic approaches and focuses critical attention on a priori modeling and the selection of a good approximating model that best represents the inference supported by the data. Kullback-Leibler Information represents a fundamental quantity in science  Read more...
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Details

Material Type: Internet resource
Document Type: Book, Internet Resource
All Authors / Contributors: Kenneth P Burnham; David Raymond Anderson
ISBN: 0387953647 9780387953649
OCLC Number: 48557578
Notes: Revised edition of: Model selection and inference. c1998.
Description: xxvi, 488 pages : illustrations ; 24 cm
Contents: 1. Introduction --
2. Information and likelihood theory: a basis for model selection and inference --
3. Basic use of the information-theoretic approach --
4. Formal inference from more than one model: multimodel inference (MMI) --
5. Monte Carlo insights and extended examples --
6. Advanced issues and deeper insights --
7. Statistical theory and numerical results --
8. Summary.
Responsibility: Kenneth P. Burnham, David R. Anderson.
More information:

Abstract:

A unique and comprehensive text on the philosophy of model-based data analysis and strategy for the analysis of empirical data. The book introduces information theoretic approaches and focuses  Read more...

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