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