This paper develops a procedure based on Expected Posterior Priors to perform Bayesian model comparison for discrete undirected decomposable graphical models. The basic idea is that priors should not be assigned separately under each model; rather they should be related across models, in order to acquire some degree of compatibility, and thus allow fairer and more robust comparisons. The methodology is illustrated through the analysis of a 2 x 3 x 4 contingency table.

Expected posterior priors for model comparison in a class of discrete graphical models

LUPPARELLI, MONIA
2009

Abstract

This paper develops a procedure based on Expected Posterior Priors to perform Bayesian model comparison for discrete undirected decomposable graphical models. The basic idea is that priors should not be assigned separately under each model; rather they should be related across models, in order to acquire some degree of compatibility, and thus allow fairer and more robust comparisons. The methodology is illustrated through the analysis of a 2 x 3 x 4 contingency table.
Proceedings of Complex Modelling and computationally intensive statistical methods for estimation and prediction
127
132
Consonni G.; Lupparelli M.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/79648
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