Statistics and Computing

, Volume 12, Issue 1, pp 27–36

On Bayesian model and variable selection using MCMC

  • Petros Dellaportas
  • Jonathan J. Forster
  • Ioannis Ntzoufras
Article

DOI: 10.1023/A:1013164120801

Cite this article as:
Dellaportas, P., Forster, J.J. & Ntzoufras, I. Statistics and Computing (2002) 12: 27. doi:10.1023/A:1013164120801
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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.

Gibbs sampler independence sampler Metropolis–Hastings reversible jump 

Copyright information

© Kluwer Academic Publishers 2002

Authors and Affiliations

  • Petros Dellaportas
  • Jonathan J. Forster
  • Ioannis Ntzoufras

There are no affiliations available

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