Skip to Main content Skip to Navigation
Reports

Deviance Information Criteria for Missing Data Models

Gilles Celeux 1 Florence Forbes 1 Christian Robert 1 Mike Titterington 1
1 IS2 - Statistical Inference for Industry and Health
Inria Grenoble - Rhône-Alpes, LBBE - Laboratoire de Biométrie et Biologie Evolutive - UMR 5558
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.
Document type :
Reports
Complete list of metadata

https://hal.inria.fr/inria-00071724
Contributor : Rapport de Recherche Inria <>
Submitted on : Tuesday, May 23, 2006 - 6:36:41 PM
Last modification on : Monday, February 10, 2020 - 4:36:45 PM
Long-term archiving on: : Sunday, April 4, 2010 - 10:35:11 PM

Identifiers

  • HAL Id : inria-00071724, version 1

Collections

Citation

Gilles Celeux, Florence Forbes, Christian Robert, Mike Titterington. Deviance Information Criteria for Missing Data Models. [Research Report] RR-4859, INRIA. 2003. ⟨inria-00071724⟩

Share

Metrics

Record views

279

Files downloads

816