統計数理研究所

Abstract: The expected auxiliary variable method is a general framework for Monte Carlo simulation in situations where the target distribution of interest is intractable thus preventing the implementation of classical methods.
The method finds application in situations where marginal computations are of interest, trans-dimensional move design is difficult in model selection setups or when the normalizing constant of a particular distribution is unknown but required for exact computations.
I will present a general construction that allows us to use the expected auxiliary variable method in a very wide range of applications. Several applications where Bayesian computation was previously impossible will be presented.