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1992•Journal of Computational and Graphical StatisticsRequires access

Numerical Computation of Multivariate Normal Probabilities

Alan C. Genz

Open publisher page 966 citations

Abstract

The numerical computation of a multivariate normal probability is often a difficult problem. This article describes a transformation that simplifies the problem and places it into a form that allows efficient calculation using standard numerical multiple integration algorithms. Test results are presented that compare implementations of two algorithms that use the transformation with currently available software.

About this research paper

What this paper is about

The numerical computation of a multivariate normal probability is often a difficult problem. This article describes a transformation that simplifies the problem and places it into a form that allows efficient calculation using standard numerical multiple integration algorithms. Test results are presented that compare implementations of two algorithms that use the transformation with currently available software.

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OpenAlex reports 966 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

The numerical computation of a multivariate normal probability is often a difficult problem. This article describes a transformation that simplifies the problem and places it into a form that allows efficient calculation using standard numerical multiple integration algorithms. Test results are presented that compare implementations of two algorithms that use the transformation with currently available software.

Key concepts: Multivariate normal distribution, Computation, Multivariate statistics, Transformation (genetics), Computer science, Algorithm, Software, Normal distribution

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