A multi-point Metropolis scheme with generic weight functions

Luca Martino, Victor Pascual Del Olmo and Jesse Read

Statistics & Probability Letters, 2012, vol. 82, issue 7, 1445-1453

Abstract: The multi-point Metropolis algorithm is an advanced MCMC technique based on drawing several correlated samples at each step and choosing one of them according to some normalized weights. We propose a variation of this technique where the weight functions are not specified, i.e., the analytic form can be chosen arbitrarily. This has the advantage of greater flexibility in the design of high-performance MCMC samplers. We prove that our method fulfills the balance condition, and provide a numerical simulation. We also give new insight into the functionality of different MCMC algorithms, and the connections between them.

Keywords: Multiple Try Metropolis algorithm; Multi-point Metropolis algorithm; MCMC methods (search for similar items in EconPapers)
Date: 2012
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Citations: View citations in EconPapers (6)

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DOI: 10.1016/j.spl.2012.04.008

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