Bayesian computation via the Gibbs sampler and related Markov chain Monte Carlo methods. (English) Zbl 0779.62030

Smith, A. F. M.; Roberts, G. O.

J. R. Stat. Soc., Ser. B 55, No. 1, 3-23 (1993).

Summary: The use of the Gibbs sampler for Bayesian computation is reviewed and illustrated in the context of some canonical examples. Other Markov chain Monte Carlo simulation methods are also briefly described, and comments are made on the advantages of sample-based approaches for Bayesian inference summaries.

MSC:

62F15	Bayesian inference
65C99	Probabilistic methods, stochastic differential equations
62M99	Inference from stochastic processes

Keywords:

censored data; constrained parameter models; generalized linear models; Hastings algorithm; hierarchical models; missing data; time series models; review; Gibbs sampler; Bayesian computation; Markov chain Monte Carlo simulation methods; sample-based approaches