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Generation of a Multivariate Distribution for Specified Univariate Marginals and Covariance Structure.

I. R. Goodman

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Abstract

This paper addresses the problem of determining and generating outcomes for a joint multivariate distribution having specified arbitrary marginal distributions and correlation structure. in addition, a new technique is developed which generates outcome for essentially any given multivariate random variable from a more conveniently realizable random variable. This generalizes in a natural way the well known univariate transformation of probability sampling technique. (Author)

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What this paper is about

This paper addresses the problem of determining and generating outcomes for a joint multivariate distribution having specified arbitrary marginal distributions and correlation structure. in addition, a new technique is developed which generates outcome for essentially any given multivariate random variable from a more conveniently realizable random variable. This generalizes in a natural way the well known univariate transformation of probability sampling technique. (Author)

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Available abstract

This paper addresses the problem of determining and generating outcomes for a joint multivariate distribution having specified arbitrary marginal distributions and correlation structure. in addition, a new technique is developed which generates outcome for essentially any given multivariate random variable from a more conveniently realizable random variable. This generalizes in a natural way the well known univariate transformation of probability sampling technique. (Author)

Key concepts: Univariate, Univariate distribution, Multivariate statistics, Marginal distribution, Mathematics, Multivariate t-distribution, Covariance, Joint probability distribution

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