A comprehensive text on the philosophy of model-based data analysis and strategy for the analysis of empirical data. It 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. Num Pages: 488 pages, 51 black & white tables, biography. BIC Classification: PBWH; PDE; TBJ. Category: (P) Professional & Vocational. Dimension: 239 x 163 x 34. Weight in Grams: 934. . 2002. 2nd ed. 2002. Corr. 3rd printing 2003. Hardback. . . . . Books ship from the US and Ireland. N� de ref. del art�culo V9780387953649

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T�tulo: Model Selection and Multi-model Inference

Editorial: Springer-Verlag New York Inc.

A�o de publicaci�n: 2002

Encuadernaci�n: Encuadernaci�n de tapa dura

Condici�n: New

Edici�n: 2� Edici�n

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Sinopsis:

Book by Kenneth P Burnham David Anderson

Rese�a del editor:

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.

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