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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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autores principales: Konishi, Sadanori (Autor), Kitagawa, Genshiro (Autor)
Autor Corporativo: SpringerLink (Online service)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: New York, NY : Springer New York : Imprint: Springer, 2008.
Edición:1st ed. 2008.
Colección:Springer Series in Statistics,
Temas:
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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