PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Deviance information criteria for missing data models
Gilles Celeux, Florence Forbes, Christian P Robert and Mike D Titterington
Bayesian Analysis 2005.

Abstract

The deviance information criterion (DIC) introduced by is directly inspired by linear and generalised linear models, but it is not so naturally defined for missing data models. In this paper, we reassess the criterion for such models, testing the behaviour of various extensions in the cases of mixture and random effect models.

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EPrint Type:Article
Additional Information:Model Selection
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Theory & Algorithms
ID Code:1853
Deposited By:Gilles Celeux
Deposited On:29 November 2005