Model Selection and Multimodel Inference - A Practical Information-Theoretic Approach (Paperback, Softcover reprint of the original 2nd ed. 2002)

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.

General

Imprint:	Springer-Verlag New York
Country of origin:	United States
Release date:	December 2010
First published:	2002
Authors:	Kenneth P. Burnham • David R Anderson
Dimensions:	235 x 155 x 27mm (L x W x T)
Format:	Paperback
Pages:	488
Edition:	Softcover reprint of the original 2nd ed. 2002
ISBN-13:	978-1-4419-2973-0
Categories:	Books > Science & Mathematics > Mathematics > Probability & statistics Books > Science & Mathematics > Biology, life sciences > Life sciences: general issues > Ecological science, the Biosphere
LSN:	1-4419-2973-8
Barcode:	9781441929730

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