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An Adaptive Version for the Metropolis Adjusted Langevin Algorithm with a Truncated Drift

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Author Info
Yves Atchade () (Department of Mathematics and Statistics, University of Ottawa and LRSP)

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Abstract

This paper proposes an adaptive version for the Metropolis adjusted Langevin algorithm with a truncated drift (T-MALA). The scale parameter and the covariance matrix of the proposal kernel of the algorithm are simultaneously and recursively updated in order to reach the optimal acceptance rate of 0:574 (see Roberts and Rosenthal (2001)) and to estimate and use the correlation structure of the target distribution. We develop some convergence results for the algorithm. A simulation example is presented.

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File URL: http://www.repad.org/ca/on/lrsp/csa2.pdf
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File Function: First version, 2005
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Publisher Info
Paper provided by Département des sciences administratives, UQO in its series RePAd Working Paper Series with number LRSP-WP1.

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Length: 14 pages
Date of creation: 01 Mar 2005
Date of revision:
Handle: RePEc:pqs:wpaper:0272005

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Related research
Keywords: Markov Chain Monte Carlo Stochastic approximation algorithms Metropolis Adjusted Langevin algorithm geometric rate of convergence.

Find related papers by JEL classification:
C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - General
C40 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - General

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This page was last updated on 2008-11-17.

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