Rare events simulation for heavy-tailed distributions
Rare events simulation for heavy-tailed distributions
复制标题
重尾分布的罕见事件模拟
DOI：
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发表时间：
2000
期刊：
影响因子：
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通讯作者：
Bjarne Højgaard
中科院分区：
文献类型：
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作者：
S. Asmussen;K. Binswanger;Bjarne Højgaard
本文研究了重尾情况下的罕见事件模拟，其中一些基本分布不具有轻尾情况下标准算法所需的指数矩。几个反例表明，在重尾的情况下，有严重的问题与发展的限制结果的条件分布的方法，给定的罕见事件，这是用来作为重要性抽样的基础。在积极的一面，有一个相对误差几乎是有界的两个算法，一个基于顺序统计量和其他不同的重要性抽样的想法。
This paper studies rare events simulation for the heavy-tailed case, where some of the underlying distributions fail to have the exponential moments required for the standard algorithms for the lighttailed case. Several counterexamples are given to indicate that in the heavy-tailed case, there are severe problems with the approach of developing limit results for the conditional distribution given the rare event; this is used as a basis for importance sampling. On the positive side, two algorithms having a relative error which is almost bounded are presented, one based upon order statistics and the other upon a different importance sampling idea.