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2007 On the efficiency of adaptive MCMC algorithms
Christophe Andrieu, Yves Atchade
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Electron. Commun. Probab. 12: 336-349 (2007). DOI: 10.1214/ECP.v12-1320

Abstract

We study a class of adaptive Markov Chain Monte Carlo (MCMC) processes which aim at behaving as an ``optimal'' target process via a learning procedure. We show, under appropriate conditions, that the adaptive MCMC chain and the ``optimal'' (nonadaptive) MCMC process share many asymptotic properties. The special case of adaptive MCMC algorithms governed by stochastic approximation is considered in details and we apply our results to the adaptive Metropolis algorithm of [Haario, Saksman, Tamminen].

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Christophe Andrieu. Yves Atchade. "On the efficiency of adaptive MCMC algorithms." Electron. Commun. Probab. 12 336 - 349, 2007. https://doi.org/10.1214/ECP.v12-1320

Information

Accepted: 12 October 2007; Published: 2007
First available in Project Euclid: 6 June 2016

zbMATH: 1129.65006
MathSciNet: MR2350572
Digital Object Identifier: 10.1214/ECP.v12-1320

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