Information criteria and statistical modeling pdf

5.46  ·  8,786 ratings  ·  273 reviews
information criteria and statistical modeling pdf

Akaike information criterion - Wikipedia

This content was uploaded by our users and we assume good faith they have the permission to share this book. If you own the copyright to this book and it is wrongfully on our website, we offer a simple DMCA procedure to remove your content from our site. Start by pressing the button below! Springer Series in Statistics Advisors: P. Bickel, P. Diggle, S. Fienberg, U.
File Name: information criteria and statistical modeling
Size: 42221 Kb
Published 10.01.2019

Model Selection With AIC

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. A secondary objective is to provide a theoretical basis for the analysis and extension of information criteria via a statistical functional approach.

Akaike information criterion

The problem of evaluating the goodness of statistical models is fundamental and of importance in various fields of statistics, natural sciences, neural networks, engineering, economics, etc. AIC is a criterion for evaluating the models estimated by the maximum likelihood method. With the development of various non-linear modeling techniques, the construction of criteria which enable us to evaluate various types of statistical models has been required. The aim of this paper is to give a systematic account of some recent developments in model evaluation criteria from information-theoretic and Bayesian points of views. We intend to provide a basic expository account of the fundamental principles behind information criteria. We also discuss the application of the bootstrap methods in model evaluation problems. Already have an account?

Navigation menu

It seems that you're in Germany. - The Akaike information criterion AIC is an estimator of the relative quality of statistical models for a given set of data.




  1. Gill D. says:

    A book from the sky snapshot anne rice cry to heaven pdf

  2. Jewel R. says:

    Information Criteria and Statistical Modeling - PDF Free Download

Leave a Reply

Your email address will not be published. Required fields are marked *