Article ID: | iaor19951972 |
Country: | Switzerland |
Volume: | 56 |
Issue: | 1 |
Start Page Number: | 1 |
End Page Number: | 13 |
Publication Date: | Jun 1995 |
Journal: | Annals of Operations Research |
Authors: | Berger J.O., Salinetti G. |
Keywords: | Bayesian modelling |
Solving Bayesian decision problems usually requires approximation procedures, all leading to study the convergence of the approximating infima. This aspect is analysed in the context of epigraphical convergence of integral functionals, as minimal context for convergence of infima. The results, applied to the Monte Carlo importance sampling, give a necessary and sufficient condition for convergence of the approximations of Bayes decision problems and sufficient conditions for a large class of Bayesian statistical decision problems.