1993Journal of the Royal Statistical Society Series B (Statistical Methodology)Requires access

Characterizing a Joint Probability Distribution by Conditionals

Andrew Gelman, Terence P. Speed

Open publisher page 108 citations

Abstract

SUMMARY We derive conditions under which a set of conditional and marginal probability distributions will uniquely specify an all-positive joint distribution. Our theoretical result may yield insights into the construction and simulation of multivariate probability models.

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SUMMARY We derive conditions under which a set of conditional and marginal probability distributions will uniquely specify an all-positive joint distribution. Our theoretical result may yield insights into the construction and simulation of multivariate probability models.

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OpenAlex reports 108 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

SUMMARY We derive conditions under which a set of conditional and marginal probability distributions will uniquely specify an all-positive joint distribution. Our theoretical result may yield insights into the construction and simulation of multivariate probability models.

Key concepts: Joint probability distribution, Marginal distribution, Probability distribution, Multivariate statistics, Conditional probability, Conditional probability distribution, Mathematics, Joint (building)

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