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BAYESIAN MODEL SELECTION

Traditionally, Bayes factors, posterior odds and posterio r model probabilities are used in Bayesian model selection. This approach has, however, the problem that the conclusions are often too sensitive to prior specifications. Another approach is to use discrepancy measures in model comparison and posterior predictive checks in the assesment of model adequecy. These approaches are briefly summarized and an illustrative example provided.