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
收藏
页码：422 / 428
页数：7
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