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...

Full description

Main Authors: Konishi, Sadanori. (Author, http://id.loc.gov/vocabulary/relators/aut), Kitagawa, Genshiro. (http://id.loc.gov/vocabulary/relators/aut)
Corporate Author: SpringerLink (Online service)
Language:English
Published: New York, NY : Springer New York : Imprint: Springer, 2008.
Edition:1st ed. 2008.
Series:Springer Series in Statistics,
Subjects:
Online Access:https://doi.org/10.1007/978-0-387-71887-3
LEADER 05299nam a22006135i 4500
001 978-0-387-71887-3
003 DE-He213
005 20210616215632.0
007 cr nn 008mamaa
008 100301s2008 xxu| s |||| 0|eng d
020 |a 9780387718873  |9 978-0-387-71887-3 
024 7 |a 10.1007/978-0-387-71887-3  |2 doi 
050 4 |a QA276-280 
072 7 |a PBT  |2 bicssc 
072 7 |a MAT029000  |2 bisacsh 
072 7 |a PBT  |2 thema 
082 0 4 |a 519.5  |2 23 
100 1 |a Konishi, Sadanori.  |e author.  |4 aut  |4 http://id.loc.gov/vocabulary/relators/aut 
245 1 0 |a Information Criteria and Statistical Modeling  |h [electronic resource] /  |c by Sadanori Konishi, Genshiro Kitagawa. 
250 |a 1st ed. 2008. 
264 1 |a New York, NY :  |b Springer New York :  |b Imprint: Springer,  |c 2008. 
300 |a XII, 276 p.  |b online resource. 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
347 |a text file  |b PDF  |2 rda 
490 1 |a Springer Series in Statistics,  |x 0172-7397 
505 0 |a 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. 
520 |a 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 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. 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. 
650 0 |a Statistics . 
650 0 |a Mathematical models. 
650 0 |a Coding theory. 
650 0 |a Information theory. 
650 0 |a Data mining. 
650 0 |a Mathematical statistics. 
650 0 |a Computer simulation. 
650 1 4 |a Statistical Theory and Methods.  |0 https://scigraph.springernature.com/ontologies/product-market-codes/S11001 
650 2 4 |a Mathematical Modeling and Industrial Mathematics.  |0 https://scigraph.springernature.com/ontologies/product-market-codes/M14068 
650 2 4 |a Coding and Information Theory.  |0 https://scigraph.springernature.com/ontologies/product-market-codes/I15041 
650 2 4 |a Data Mining and Knowledge Discovery.  |0 https://scigraph.springernature.com/ontologies/product-market-codes/I18030 
650 2 4 |a Probability and Statistics in Computer Science.  |0 https://scigraph.springernature.com/ontologies/product-market-codes/I17036 
650 2 4 |a Simulation and Modeling.  |0 https://scigraph.springernature.com/ontologies/product-market-codes/I19000 
700 1 |a Kitagawa, Genshiro.  |e author.  |4 aut  |4 http://id.loc.gov/vocabulary/relators/aut 
710 2 |a SpringerLink (Online service) 
773 0 |t Springer Nature eBook 
776 0 8 |i Printed edition:  |z 9781441924568 
776 0 8 |i Printed edition:  |z 9780387518978 
776 0 8 |i Printed edition:  |z 9780387718866 
830 0 |a Springer Series in Statistics,  |x 0172-7397 
856 4 0 |u https://doi.org/10.1007/978-0-387-71887-3 
912 |a ZDB-2-SMA 
912 |a ZDB-2-SXMS 
950 |a Mathematics and Statistics (SpringerNature-11649) 
950 |a Mathematics and Statistics (R0) (SpringerNature-43713)