Model selection and multimodel inference : a practical information-theoretic approach

Kenneth P. Burnham, David R. Anderson

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 critical attention on a priori modeling and the selection of a good approximating model that best represents the inference supported by the data. It contains several new approaches to estimating model selection uncertainty and incorporating selection uncertainty into estimates of precision. An array of examples is given to illustrate various technical issues. The text has been written for biologists and statisticians using models for making inferences from empirical data.

「Nielsen BookData」より

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 critical attention on a priori modeling and the selection of a good approximating model that best represents the inference supported by the data. It contains several new approaches to estimating model selection uncertainty and incorporating selection uncertainty into estimates of precision. An array of examples is given to illustrate various technical issues. The text has been written for biologists and statisticians using models for making inferences from empirical data.

「Nielsen BookData」より

[目次]

  • Introduction * Information and Likelihood Theory: A Basis for Model Selection and Inference * Basic Use of the Information-Theoretic Approach * Formal Inference From More Than One Model: Multi-Model Inference (MMI) * Monte Carlo Insights and Extended Examples * Statistical Theory and Numerical Results * Summary

「Nielsen BookData」より

[目次]

  • Introduction * Information and Likelihood Theory: A Basis for Model Selection and Inference * Basic Use of the Information-Theoretic Approach * Formal Inference From More Than One Model: Multi-Model Inference (MMI) * Monte Carlo Insights and Extended Examples * Statistical Theory and Numerical Results * Summary

「Nielsen BookData」より

この本の情報

書名 Model selection and multimodel inference : a practical information-theoretic approach
著作者等 Anderson, David R.
Burnham, Kenneth P.
Anderson David R.
書名別名 Model selection and inference : a practical information-theoretic approach
出版元 Springer
刊行年月 c2002
版表示 2nd ed
ページ数 xxvi, 488 p.
大きさ 24 cm
ISBN 9781441929730
9780387953649
NCID BA58633902
※クリックでCiNii Booksを表示
言語 英語
出版国 アメリカ合衆国
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