Normal view MARC view ISBD view

Information criteria and statistical modeling

By: Konishi, Sadanori.
Material type: materialTypeLabelBookPublisher: New York Springer Science+Business Media 2008Description: xii, 273 p. : ill. ; 24 cm.ISBN: 9780387718866.Subject(s): Information modeling | Mathematical analysis | Stochastic analysisDDC classification: 519.22 Summary: 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. (http://www.springer.com/statistics/statistical+theory+and+methods/book/978-0-387-71886-6)
Tags from this library: No tags from this library for this title. Log in to add tags.
    average rating: 0.0 (0 votes)
Item type Current location Item location Call number Status Date due Barcode
Books Vikram Sarabhai Library
Slot 1403 (0 Floor, East Wing) 519.22 K6I6 (Browse shelf) Available 173700

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. (http://www.springer.com/statistics/statistical+theory+and+methods/book/978-0-387-71886-6)

There are no comments for this item.

Log in to your account to post a comment.

Powered by Koha