基于偏生建议的矩匹配自适应重要性抽样

IF 0.8 Q3 STATISTICS & PROBABILITY

Monte Carlo Methods and Applications Pub Date : 2022-02-15 DOI:10.1515/mcma-2022-2106

Shijia Wang, T. Swartz

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引用次数: 2

摘要

摘要本文考虑了重要性抽样的积分逼近方法，其中重要性抽样器从一组偏生分布中选取。这是与重要性抽样应用程序中通常考虑的分布不同的另一类分布。我们描述了变量的产生，并提出了自适应的方法来拟合偏生族的一个成员到一个特定的积分。我们还在几个示例中演示了该方法的实用性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Moment matching adaptive importance sampling with skew-student proposals

Abstract This paper considers integral approximation via importance sampling where the importance sampler is chosen from a family of skew-Student distributions. This is an alternative class of distributions than is typically considered in importance sampling applications. We describe variate generation and propose adaptive methods for fitting a member of the skew-Student family to a particular integral. We also demonstrate the utility of the approach in several examples.

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来源期刊

Monte Carlo Methods and Applications STATISTICS & PROBABILITY-

CiteScore

1.20

自引率

22.20%

发文量