Abstract
Several MCMC methods have been proposed for estimating probabilities of models and associated 'model-averaged' posterior distributions in the presence of model uncertainty. We discuss, compare, develop and illustrate several of these methods, focussing on connections between them.
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Dellaportas, P., Forster, J.J. & Ntzoufras, I. On Bayesian model and variable selection using MCMC. Statistics and Computing 12, 27–36 (2002). https://doi.org/10.1023/A:1013164120801
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DOI: https://doi.org/10.1023/A:1013164120801