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April 2009 The pseudo-marginal approach for efficient Monte Carlo computations
Christophe Andrieu, Gareth O. Roberts
Ann. Statist. 37(2): 697-725 (April 2009). DOI: 10.1214/07-AOS574


We introduce a powerful and flexible MCMC algorithm for stochastic simulation. The method builds on a pseudo-marginal 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.


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Christophe Andrieu. Gareth O. Roberts. "The pseudo-marginal approach for efficient Monte Carlo computations." Ann. Statist. 37 (2) 697 - 725, April 2009.


Published: April 2009
First available in Project Euclid: 10 March 2009

zbMATH: 1185.60083
MathSciNet: MR2502648
Digital Object Identifier: 10.1214/07-AOS574

Primary: 60J22 , 60K35
Secondary: 60K35

Keywords: auxiliary variable , convergence , marginal , Markov chain Monte Carlo

Rights: Copyright © 2009 Institute of Mathematical Statistics


Vol.37 • No. 2 • April 2009
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