Model Selection and Multimodel Inference : A Practical Information-Theoretic Approach
Softcover reprint of the original 2nd ed. 2002
Book Details
Format
Paperback / Softback
ISBN-10
1441929738
ISBN-13
9781441929730
Edition
Softcover reprint of the original 2nd ed. 2002
Publisher
Springer-Verlag New York Inc.
Imprint
Springer-Verlag New York Inc.
Country of Manufacture
US
Country of Publication
GB
Publication Date
Dec 1st, 2010
Print length
488 Pages
Weight
742 grams
Dimensions
23.20 x 15.70 x 2.70 cms
Product Classification:
Probability & statisticsProbability and statisticsEcological science, the Biosphere
Ksh 34,750.00
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However, we now emphasize that information-theoretic approaches allow formal inference to be based on more than one model (m- timodel inference). S- ond, concepts related to making formal inferences from more than one model (multimodel inference) have been emphasized throughout the book, but p- ticularly in Chapters 4, 5, and 6.
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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