Computing posterior upper expectations

This article investigates the computation of posterior upper expectations i nduced by imprecise probabilities, with emphasis on the effects of irreleva nce and independence judgements. Algorithms that handle imprecise priors an d imprecise likelihoods are reviewed, and a new result on the limiting dive rgence of posterior upper probabilities is presented. Algorithms that handl e irrelevance and independence relations in multivariate models are analyze d through graphical representations, inspired by the popular Bayesian netwo rk model. (C) 2000 Elsevier Science Inc. All rights reserved.