SuSTaIn
About
News
Postgraduate degrees
Events
Research highlights
Jobs
Management
Statistics Group
Statistics Home
Research
Members
Seminars
Mathematics Home
External Links
APTS
Complexity science
Royal Statistical Society
International Society for Bayesian Analysis

The pseudomarginal approach for efficient Monte Carlo computationsby Christophe Andrieu and Gareth Roberts
We introduce a powerful and flexible MCMC algorithm for stochastic simulation. The method builds on a pseudomarginal method originally introduced in [Genetics 164 (2003) 1139–1160], showing how algorithms which are approximations to an idealized marginal algorithm, can share the same marginal stationary distribution as the idealized method. Theoretical results are given describing the convergence properties of the proposed method, and simple numerical examples are given to illustrate the promising empirical characteristics of the technique. Interesting comparisons with a more obvious, but inexact, Monte Carlo approximation to the marginal algorithm, are also given. 