On Bayesian model and variable selection using MCMC
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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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- On Bayesian model and variable selection using MCMC
Statistics and Computing
Volume 12, Issue 1 , pp 27-36
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- Gibbs sampler
- independence sampler
- reversible jump
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