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
收藏
页码：79 / 83
页数：5
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