Gibbs sampling in Bayesian networks

摘要

Posterior probabilities in Bayesian networks can be evaluated by stochastic simulation. It is shown that the stochastic simulation can be viewed as a sampling from the Gibbs distribution. This view is useful in (1) making statements about convergence of the simulation and (2) finding the most likely instantiation of the Bayesian network.