On the construction of minimum information bivariate copula families

Tim Bedford and Kevin Wilson ()

Annals of the Institute of Statistical Mathematics, 2014, vol. 66, issue 4, 703-723

Abstract: Copulas have become very popular as modelling tools in probability applications. Given a finite number of expectation constraints for functions defined on the unit square, the minimum information copula is that copula which has minimum information (Kullback–Leibler divergence) from the uniform copula. This can be considered the most “independent” copula satisfying the constraints. We demonstrate the existence and uniqueness of such copulas, rigorously establish the relation with discrete approximations, and prove an unexpected relationship between constraint expectation values and the copula density formula. Copyright The Institute of Statistical Mathematics, Tokyo 2014

Keywords: Bivariate copulas; Information; Uncertainty modelling; Expert judgement (search for similar items in EconPapers)
Date: 2014
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Citations: View citations in EconPapers (3)

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DOI: 10.1007/s10463-013-0422-0

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