Issues in the Multiple Try Metropolis mixing

Autor(es)

Martino, L. ; Louzada, F.

• Tipo de documento: Artigo Científico
• Fonte: Computational Statistics; v. 32, n. 1, p. 239-252, MAR 2017.
• Citações Web of Science: 5

Resumo

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. (AU)

• Processo FAPESP: 14/23160-6 - Esquemas eficientes de Monte Carlo para espaços de alta dimensão e grandes bancos de dados médicos e industriais
• Beneficiário: Luca Martino
• Modalidade de apoio: Bolsas no Brasil - Pós-Doutorado