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£102.31

Springer Information Criteria and Statistical Modeling (Springer Series in Statistics)

Name: Information Criteria and Statistical Modeling (Springer Series in Statistics)
Brand: Springer
Price: 102.31 GBP
Availability: InStock

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Data Mining

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Description

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.

Product Specifications

Brand: Springer
Model: Refer to Sapnet.
Format: hardcover
ASIN: 0387718869
Category: Books > Subjects > Computing & Internet > Databases > Data Storage & Management > Data Mining
Domain: Amazon UK
Release Date: 12 October 2007
Listed Since: 07 May 2007

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Springer Information Criteria and Statistical Modeling (Springer Series in Statistics)

About as cheap as it gets. The only time it was cheaper was 3 months ago.

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