Model Selection and Inference von Kenneth P. Burnham | A Practical Information-Theoretic Approach | ISBN 9780387985046

Model Selection and Inference

A Practical Information-Theoretic Approach

von Kenneth P. Burnham und David R. Anderson
Mitwirkende
Autor / AutorinKenneth P. Burnham
Autor / AutorinDavid R. Anderson
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Buchcover Model Selection and Inference | Kenneth P. Burnham | EAN 9780387985046 | ISBN 0-387-98504-2 | ISBN 978-0-387-98504-6

From the reviews of the second edition:

Burnham and Anderson (eschew) P-values completely and (focus) entirely on how to decide when a model or models adequately fits the data. In essence, this is what an ecologist wants to know-how do predictive models work? This simple categorization, however, belies the conceptual richness that Burnham and Anderson present in their book, and its importance.„ (Ecology)

“Bolstered by a new chapter and an additional 140 pages, this very specialized book is now quite a sizable affair in its second edition … . Subtitled ‘A Practical Information-Theoretic Approach,’ the book is built on the use of the Kullback-Leibler distance approach for multimodel inference. … The enthusiasm of the authors for their subject is apparent from the effort that they have made to extensively revise what already was a very unique book … ." (Technometrics, Vol. 54 (2), May, 2003)

Model Selection and Inference

A Practical Information-Theoretic Approach

von Kenneth P. Burnham und David R. Anderson
Mitwirkende
Autor / AutorinKenneth P. Burnham
Autor / AutorinDavid R. Anderson
Statisticians and applied scientists must often select a model to fit empirical data. This book discusses the philosophy and strategy of selecting such a model using the information theory approach pioneered by Hirotugu Akaike. This approach focuses critical attention on a priori modeling and the selection of a good approximating model that best represents the inference supported by the data. The book includes practical applications in biology and environmental science.