mvtnorm: New numerical algorithm for multivariate normal probabilities

IF 2.3 4区 计算机科学 Q3 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
R Journal Pub Date : 2009-01-01 DOI:10.15488/3835
Xuefei Mi, Tetsuhisa Miwa, T. Hothorn
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引用次数: 33

Abstract

Miwa et al. (2003) proposed a numerical algorithm for evaluating multivariate normal probabilities. Starting with version 0.9-0 of the mvtnorm package (Hothorn et al., 2001; Genz et al., 2008), this algorithm is available to the R community. We give a brief introduction to Miwa’s procedure and compare it, with respect to computing time and accuracy, to a quasi-randomized Monte-Carlo procedure proposed by Genz and Bretz (1999), which has been available through mvtnorm for some years now. The new algorithm is applicable to problems with dimension smaller than 20, whereas the procedures by Genz and Bretz (1999) can be used to evaluate 1000-dimensional normal distributions. At the end of this article, a suggestion is given for choosing a suitable algorithm in different situations.
mvtnorm:多元正态概率的新数值算法
Miwa等人(2003)提出了一种评估多元正态概率的数值算法。从mvtnorm包的0.9-0版本开始(Hothorn et al., 2001;Genz et al., 2008),该算法可供R社区使用。我们简要介绍了Miwa的程序,并将其与Genz和Bretz(1999)提出的准随机蒙特卡罗程序进行了比较,该程序已通过mvtnorm提供了多年。新算法适用于小于20维的问题,而Genz和Bretz(1999)的程序可用于评估1000维的正态分布。在本文的最后,给出了在不同情况下选择合适算法的建议。
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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来源期刊
R Journal
R Journal COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS-STATISTICS & PROBABILITY
CiteScore
2.70
自引率
0.00%
发文量
40
审稿时长
>12 weeks
期刊介绍: The R Journal is the open access, refereed journal of the R project for statistical computing. It features short to medium length articles covering topics that should be of interest to users or developers of R. The R Journal intends to reach a wide audience and have a thorough review process. Papers are expected to be reasonably short, clearly written, not too technical, and of course focused on R. Authors of refereed articles should take care to: - put their contribution in context, in particular discuss related R functions or packages; - explain the motivation for their contribution; - provide code examples that are reproducible.
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