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130626  eng 
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a 9780387718873

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1 

a Konishi, Sadanori

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0 
0 
a Information Criteria and Statistical Modeling
h Elektronische Ressource
c by Sadanori Konishi, Genshiro Kitagawa

250 


a 1st ed. 2008

260 


a New York, NY
b Springer New York
c 2008, 2008

300 


a XII, 276 p
b online resource

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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

653 


a Mathematical statistics

653 


a Coding and Information Theory

653 


a Statistical Theory and Methods

653 


a Coding theory

653 


a Computer science / Mathematics

653 


a Probability and Statistics in Computer Science

653 


a Computer simulation

653 


a Statistics

653 


a Computer Modelling

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a Data mining

653 


a Information theory

653 


a Mathematical Modeling and Industrial Mathematics

653 


a Data Mining and Knowledge Discovery

653 


a Mathematical models

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1 

a Kitagawa, Genshiro
e [author]

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0 
7 
a eng
2 ISO 6392

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b Springer
a Springer eBooks 2005

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0 

a Springer Series in Statistics

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a 10.1007/9780387718873

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u https://doi.org/10.1007/9780387718873?nosfx=y
x Verlag
3 Volltext

082 
0 

a 519.5

520 


a His primary interests are in time series analysis, nonGaussian nonlinear filtering and statistical modeling. He is the executive editor of the Annals of theInstitute of Statistical Mathematics, coauthor 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

520 


a Winner of the 2009 Japan Statistical Association Publication Prize. The Akaike information criterion (AIC) derived as an estimator of the KullbackLeibler 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.

520 


a 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 coauthor 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 DirectorGeneral of the Institute of Statistical Mathematics and Professor of Statistical Science at the Graduate University for Advanced Study.
