BOUNDED RELATIVE ERROR IMPORTANCE SAMPLING AND RARE EVENT SIMULATION

被引：5

作者：

McLeish, Don L. ^{[1
]}

机构：

[1] Univ Waterloo, Dept Stat & Actuarial Sci, Waterloo, ON N2L 3G1, Canada

来源：

ASTIN BULLETIN | 2010年 / 40卷 / 01期

基金：

加拿大自然科学与工程研究理事会;

关键词：

Rare event simulation; relative error; g&h distribution; Monte Carlo methods; Importance sampling; Cross-entropy; Renyi Divergence; G-AND-H;

D O I：

10.2143/AST.40.1.2049235

中图分类号：

F [经济];

学科分类号：

02 ;

摘要：

We consider estimating tail events using exponential families of importance sampling distributions. When the cannonical sufficient statistic for the exponential family mimics the tail behaviour of the underlying cumulative distribution function, we can achieve bounded relative error for estimating tail probabilities. Examples of rare event simulation from various distributions including Tukey's g&h distribution are provided.

引用

页码：377 / 398

页数：22

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