Group for Research in Decision Analysis

Computational approaches to Bayesian model choice

Christian P. Robert ESSEC Business School, France

In this talk, we will cover recent developments of ours and of others in the computation of marginal distributions for the comparison of statistical models in a Bayesian framework. While the introduction of reversible jump MCMC by Green in 1995 is rightly perceived as the 'second MCMC revolution,' its implementation is often too complex for the problems at stake. When the number of models under study is of a reasonable magnitude, there exist computational alternatives that avoid model exploration with a reasonable efficiency and we will discuss here the pros and cons of several of those methods.

Joint work with Jean-Michel MARIN, Université Montpelliers 2, Orsay, and Nicolas CHOPIN, CREST-INSEE.