000			03322nam 2200361| 4500
001			83403
005			20211213115048.0
010			_a978-0-387-71887-3 _dcompra
090			_a83403
100			_a20190128d2008 k||y0pory50 ba
101			_aeng
102			_aUS
200			_aInformation criteria and statistical modeling _bDocumento eletrónico _fSadanori Konishi, Genshiro Kitagawa
210			_aNew York, NY _cSpringer _d2008
215			_aXII, 276 p.
225			_aSpringer Series in Statistics
300			_aColocação: Online
303			_aWinner 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.
410			_x0172-7397
606			_aEstatística matemática
606			_aTeoria de codificação
606			_aProspeção de dados
606			_aInformática
606			_aSimulação por computador
680			_aQA276
700			_aKonishi _bSadanori
701			_aKitagawa _bGenshiro _4070 _921415
801			_gRPC _aPT
856			_uhttps://doi.org/10.1007/978-0-387-71887-3
942			_2lcc _cF _n0