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Gibbs sampling in Bayesian networks. (English) Zbl 0717.68086
Summary: 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 J. Besag ‘J. Roy. Statist. Soc., Ser. B 36, 192-236 (1974; Zbl 0327.60067)] finding the most likely instantiation of the Bayesian network.

68T15 Theorem proving (deduction, resolution, etc.) (MSC2010)
60K35 Interacting random processes; statistical mechanics type models; percolation theory
68U20 Simulation (MSC2010)
Full Text: DOI
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