首页   按字顺浏览 期刊浏览 卷期浏览 Optimal estimators for the importance sampling method
Optimal estimators for the importance sampling method

 

作者: Anne Philippe,  

 

期刊: Communications in Statistics - Simulation and Computation  (Taylor Available online 2000)
卷期: Volume 29, issue 1  

页码: 97-119

 

ISSN:0361-0918

 

年代: 2000

 

DOI:10.1080/03610910008813604

 

出版商: Marcel Dekker, Inc.

 

关键词: Monte Carlo method;Accept-reject algorithm;Instrumental density;Riemann estimator

 

数据来源: Taylor

 

摘要:

The Monte Carlo method gives some estimators to evaluate the expectation [ILM0001] based on samples from either the true densityfor from some instrumental density. In this paper, we show that the Riemann estimators introduced by Philippe (1997) can be improved by using the importance sampling method. This approach produces a class of Monte Carlo estimators such that the variance is of orderO(n−2). The choice of an optimal estimator among this class is discussed. Some simulations illustrate the improvement brought by this method. Moreover, we give a criterion to assess the convergence of our optimal estimator to the integral of interest.

 

点击下载:  PDF (608KB)



返 回