Information Criteria and Statistical Modeling

• Κύριοι συγγραφείς: Konishi, Sadanori (Συγγραφέας), Kitagawa, Genshiro (Συγγραφέας)
• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: New York, NY : Springer New York, 2008.
• Σειρά: Springer Series in Statistics,
• Θέματα: Statistics.; Coding theory.; Mathematical statistics.; Data mining.; Computer simulation.; Mathematical models.; Statistical Theory and Methods.; Mathematical Modeling and Industrial Mathematics.; Coding and Information Theory.; Data Mining and Knowledge Discovery.; Probability and Statistics in Computer Science.; Simulation and 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...