Model Selection and Multimodel Inference: A Practical Information-Theoretic Approach

Burnham, Kenneth P.; Anderson, David R.

ISBN 10: 0387953647 / ISBN 13: 9780387953649

Editore: Springer, 2002

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Dati bibliografici

• Titolo: Model Selection and Multimodel Inference: A Practical Information-Theoretic Approach
• Editore: Springer
• Data di pubblicazione: 2002
• Lingua: Inglese
• ISBN 10: 0387953647
• ISBN 13: 9780387953649
• Rilegatura: Rilegato
• Edizione: seconda edizione
• Condizione: New

Descrizione articolo

Riassunto

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.

Contenuti

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