Large deviations for weighted empirical measures arising in importance sampling

STOCHASTIC PROCESSES AND THEIR APPLICATIONS

卷:126

Article

Hult, Henrik¹  Nyquist, Pierre¹ 

[1] KTH, Dept Math, S-10044 Stockholm, Sweden

关键词: Large deviations;    Empirical measures;    Importance sampling;    Monte Carlo;   

DOI  :  10.1016/j.spa.2015.08.002

来源: Elsevier

【 摘 要 】

In this paper the efficiency of an importance sampling algorithm is studied by means of large deviations for the associated weighted empirical measure. The main result, stated as a Laplace principle for these weighted empirical measures, can be viewed as an extension of Sanov's theorem. The main theorem is used to quantify the performance of an importance sampling algorithm over a collection of subsets of a given target set as well as quantile estimates. The analysis yields an estimate of the sample size needed to reach a desired precision and of the reduction in cost compared to standard Monte Carlo. (C) 2015 Published by Elsevier B.V.

【 授权许可】

Free