Issues in the Multiple Try Metropolis mixing

L. Martino () and F. Louzada
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L. Martino: Universidade de São Paulo
F. Louzada: Universidade de São Paulo

Computational Statistics, 2017, vol. 32, issue 1, No 11, 239-252

Abstract: Abstract The Multiple Try Metropolis (MTM) algorithm is an advanced MCMC technique based on drawing and testing several candidates at each iteration of the algorithm. One of them is selected according to certain weights and then it is tested according to a suitable acceptance probability. Clearly, since the computational cost increases as the employed number of tries grows, one expects that the performance of an MTM scheme improves as the number of tries increases, as well. However, there are scenarios where the increase of number of tries does not produce a corresponding enhancement of the performance. In this work, we describe these scenarios and then we introduce possible solutions for solving these issues.

Keywords: Multiple Try Metropolis algorithm; Multi-point Metropolis algorithm; MCMC methods; MTM with variable number of tries (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (2)

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DOI: 10.1007/s00180-016-0643-9

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