Measuring conformability of probabilities

D. M. Bravata, R. W. Cottle, B. C. Eaves and I. Olkin

Statistics & Probability Letters, 2001, vol. 52, issue 3, 321-327

Abstract: Given a probability space or a joint distribution, any derived probabilities or marginal distributions will be conformable. The inverse problem is to determine whether a set of fragmentary probabilities or marginal distributions is conformable in the sense that there exists a probability space or joint distribution that yields these fragmentary probabilities or marginal distributions. Because nonconformability or inconsistency may occur in a number of ways, we present a hierarchy of inconsistencies, and provide a linear programming approach designed to uncover different levels of inconsistency.

Keywords: Marginal; distributions; Fréchet; bounds; Linear; equations; Linear; programming; Consistent; probabilities (search for similar items in EconPapers)
Date: 2001
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