Akaike Information Criterion Statistics

Author: Y. Sakamoto
Editor: Springer
ISBN:
File Size: 18,77 MB
Format: PDF, Docs
Read: 3752
Download


Akaike Information Criterion Statistics
Language: en
Pages: 290
Authors: Y. Sakamoto, Masato Ishiguro, Makio Ishiguro, G. Kitagawa
Categories: Mathematics
Type: BOOK - Published: 1986-11-30 - Publisher: Springer

Books about Akaike Information Criterion Statistics
Akaike information criterion statistics
Language: en
Pages: 290
Authors: Y. Sakamoto, M. Ishiguro, G. Kitagawa
Categories: Mathematics
Type: BOOK - Published: 1984 - Publisher:

Books about Akaike information criterion statistics
Categorical Data Analysis by AIC
Language: en
Pages: 232
Authors: Y. Sakamoto
Categories: Mathematics
Type: BOOK - Published: 1992-07-31 - Publisher: Springer

This volume presents a practical and unified approach to categorical data analysis based on the Akaike Information Criterion (AIC) and the Akaike Bayesian Information Criterion (ABIC). Conventional procedures for categorical data analysis are often inappropriate because the classical test procedures employed are too closely related to specific models. The approach
Information Criteria and Statistical Modeling
Language: en
Pages: 273
Authors: Sadanori Konishi, Genshiro Kitagawa
Categories: Mathematics
Type: BOOK - Published: 2008 - Publisher: Springerverlag New York

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
Information Criteria and Statistical Modeling
Language: en
Pages: 276
Authors: Sadanori Konishi, Genshiro Kitagawa
Categories: Mathematics
Type: BOOK - Published: 2007-09-12 - Publisher: Springer Science & Business Media

Statistical modeling is a critical tool in scientific research. This book provides comprehensive explanations of the concepts and philosophy of statistical modeling, together with a wide range of practical and numerical examples. The authors expect this work to be of great value not just to statisticians but also to researchers