A multi-point Metropolis scheme with generic weight functions

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• 作者：Luca Martino ; ^{luca@tsc.uc3m.es} ; Victor Pascual Del Olmo ^{vpolmo@tsc.uc3m.es} ; Jesse Read ^{jesse@tsc.uc3m.es}
• 关键词：Multiple Try Metropolis algorithm ; Multi-point Metropolis algorithm ; MCMC methods
• 刊名：Statistics and Probability Letters
• 出版年：2012
• 期刊代码：56_01677152
• 类别：mt
• 出版时间：July, 2012
• 卷：82
• 期：7
• 页码：1445-1453
• 文件大小：425 K

摘要

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.