FITTING MIXTURE IMPORTANCE SAMPLING DISTRIBUTIONS VIA IMPROVED CROSS-ENTROPY

被引：0

作者：

Brereton, Tim J. ^{[1
]}

Chan, Joshua C. C. ^{[2
]}

Kroese, Dirk P. ^{[1
]}

机构：

[1] Univ Queensland, Dept Math, Brisbane, Qld 4072, Australia

[2] Australian Natl Univ, Res Sch Econ, GPO Box 4, Canberra, ACT 0200, Australia

来源：

PROCEEDINGS OF THE 2011 WINTER SIMULATION CONFERENCE (WSC) | 2011年

基金：

澳大利亚研究理事会;

关键词：

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In some rare-event settings, exponentially twisted distributions perform very badly. One solution to this problem is to use mixture distributions. However, it is difficult to select a good mixture distribution for importance sampling. We here introduce a simple adaptive method for choosing good mixture importance sampling distributions.

引用

页码：422 / 428

页数：7

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