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Field name	Details
Dewey Class	519.5
Title	Information Criteria and Statistical Modeling (EB) / by Sadanori Konishi, Genshiro Kitagawa.
Author	Konishi, Sadanori
Added Personal Name	Kitagawa, Genshiro
Other name(s)	SpringerLink (Online service)
Publication	New York, NY : Springer , 2008.
Physical Details	: online resource.
Series	Springer Series in Statistics 0172-7397
ISBN	9780387718873
Summary Note	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 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 Schwarzâs 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. Sadanori Konishi is Professor of Faculty of Mathematics at Kyushu University. His primary research interests are in multivariate analysis, statistical learning, pattern recognition and nonlinear statistical modeling. He is the editor of the Bulletin of Informatics and Cybernetics and is co-author of several Japanese books. He was awarded the Japan Statistical Society Prize in 2004 and is a Fellow of the American Statistical Association. Genshiro Kitagawa is Director-General of the Institute of Statistical Mathematics and Professor of Statistical Science at the Graduate University for Advanced Study. His primary interests are in time series analysis, non-Gaussian nonlinear filtering and statistical modeling. He is the executive editor of the Annals of the Institute of Statistical Mathematics, co-author of Smoothness Priors Analysis of Time Series, Akaike Information Criterion Statistics, and several Japanese books. He was awarded the Japan Statistical Society Prize in 1997 and Ishikawa Prize in 1999, and is a Fellow of the American Statistical Association.:
Contents note	Concept of statistical modeling -- Statistical models -- Information criterion -- Statistical modeling by AIC -- Generalized information criterion GIC -- Statistical modeling by GIC -- Theoretical development and asymptotic properties of the GIC -- Bootstrap information criterion -- Bayesian information criteria -- Various model evaluation criteria.
System details note	Online access to this digital book is restricted to subscription institutions through IP address (only for SISSA internal users).
Internet Site	http://dx.doi.org/10.1007/978-0-387-71887-3
Links to Related Works	Subject References: Bioinformatics . Computer simulation . Data mining . Data Mining and Knowledge Discovery . Econometrics . Mathematical Statistics . Probability and Statistics in Computer Science . Statistical Theory and Methods . Statistics . Authors: author . Kitagawa, Genshiro . Konishi, Sadanori . Corporate Authors: SpringerLink (Online service) . Series: Springer Series in Statistics . Classification: 519.5 .

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Information Criteria and Statistical Modeling

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