Sampling Exponentially Tilted Stable Distributions

被引:33
作者
Hofert, Marius [1 ]
机构
[1] Swiss Fed Inst Technol, Dept Math, CH-8092 Zurich, Switzerland
来源
ACM TRANSACTIONS ON MODELING AND COMPUTER SIMULATION | 2011年 / 22卷 / 01期
关键词
Stable distributions; exponentially tilted stable distributions; Laplace-Stieltjes transforms; sampling algorithms;
D O I
10.1145/2043635.2043638
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Several algorithms for sampling exponentially tilted positive stable distributions have recently been suggested. Three of them are known as exact methods, that is, neither do they rely on approximations nor on numerically critical procedures. One of these algorithms is outperformed by another one uniformly over all parameters. The remaining two algorithms are based on different ideas and both have their advantages. After a brief overview of sampling algorithms for exponentially tilted positive stable distributions, the two algorithms are compared. A rule is derived when to apply which for sampling these distributions.
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页数:11
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