Information Criteria and Statistical Modeling

Winner of the 2009 Japan Statistical Association Publication Prize. The Akaike information criterion (AIC) derived as an estimator of the Kullback-Leibler information discrepancy provides a useful tool for evaluating statistical models, and numerous successful applications of the AIC have been repor...

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Détails bibliographiques
Cote:Libro Electrónico
Auteurs principaux: Konishi, Sadanori (Auteur), Kitagawa, Genshiro (Auteur)
Collectivité auteur: SpringerLink (Online service)
Format: Électronique eBook
Langue:Inglés
Publié: New York, NY : Springer New York : Imprint: Springer, 2008.
Édition:1st ed. 2008.
Collection:Springer Series in Statistics,
Sujets:
Statistics .
Mathematical models.
Coding theory.
Information theory.
Data mining.
Computer science-Mathematics.
Mathematical statistics.
Computer simulation.
Statistical Theory and Methods.
Mathematical Modeling and Industrial Mathematics.
Coding and Information Theory.
Data Mining and Knowledge Discovery.
Probability and Statistics in Computer Science.
Computer Modelling.
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