Information Criteria and Statistical Modeling

Name: Information Criteria and Statistical Modeling
Brand: Springer-Verlag New York Inc.
SKU: 9780387718866
Price: 753.85 RON
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Autor: Sadanori Konishi, Genshiro Kitagawa

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Editura: Springer-Verlag New York Inc.

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The Akaike information criterion (AIC) derived as an estimator of the Kullback-Leibler information d...

Informații despre carte

Autor

Sadanori Konishi, Genshiro Kitagawa

Limbă

engleză

Legare

Carte - Copertă tare

Publicat

2007

Pagini

276

EAN

9780387718866

ISBN

0387718869

Enbook ID

01382514

Editura

Springer-Verlag New York Inc.

Greutate

606

Dimensiuni

155 x 235 x 20

Descriere completă

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 reported in various fields of natural sciences, social sciences and engineering.§One of the main objectives of this book is to provide comprehensive explanations of the concepts and derivations of the AIC and related criteria, including Schwarz s Bayesian information criterion (BIC), together with a wide range of practical examples of model selection and evaluation criteria. A secondary objective is to provide a theoretical basis for the analysis and extension of information criteria via a statistical functional approach. A generalized information criterion (GIC) and a bootstrap information criterion are presented, which provide unified tools for modeling and model evaluation for a diverse range of models, including various types of nonlinear models and model estimation procedures such as robust estimation, the maximum penalized likelihood method and a Bayesian approach.

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