A new class of interacting Markov chain Monte Carlo methods

被引：1

作者：

Del Moral, Pierre ^{[1
,2
]}

Doucet, Arnaud ^{[3
]}

机构：

[1] Univ Bordeaux, Ctr INRIA Bordeaux Sud Ouest, F-33405 Talence, France

[2] Univ Bordeaux, Inst Math Bordeaux, F-33405 Talence, France

[3] Univ British Columbia, Dept Stat, Vancouver, BC V6T 1Z2, Canada

来源：

COMPTES RENDUS MATHEMATIQUE | 2010年 / 348卷 / 1-2期

关键词：

D O I：

10.1016/j.crma.2009.11.006

中图分类号：

O1 [数学];

学科分类号：

0701 ; 070101 ;

摘要：

We present a new class of interacting Markov chain Monte Carlo methods to approximate numerically discrete-time nonlinear measure-valued equations. These stochastic processes belong to the class of self-interacting Markov chains with respect to their occupation measures. We provide several convergence results for these new methods including exponential estimates and a uniform convergence theorem with respect to the time parameter, yielding what seems to be the first results of this kind for this type of self-interacting models. We illustrate these models in the context of Feynman-Kac distribution semigroups arising in physics, biology and in statistics. (C) 2009 Academie des sciences. Published by Elsevier Masson SAS. All rights reserved.

引用

页码：79 / 83

页数：5

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