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N-dimensional measures of dependence.

Edward F. Wolff (1980)

Stochastica

In recent joint papers with B. Schweizer, we used the notion of a copula to introduce a family of symmetric, nonparametric measures of dependence of two random variables. Here, we present n-dimensional extensions of these measures and of Spearman's ro. We study them vis-a-vis appropriate higher dimensional analogues of Rényi's axioms for measures of dependence, determine relations among them, and in some cases establish reduction formulae for their computation.

New copulas based on general partitions-of-unity and their applications to risk management

Dietmar Pfeifer, Hervé Awoumlac Tsatedem, Andreas Mändle, Côme Girschig (2016)

Dependence Modeling

We construct new multivariate copulas on the basis of a generalized infinite partition-of-unity approach. This approach allows, in contrast to finite partition-of-unity copulas, for tail-dependence as well as for asymmetry. A possibility of fitting such copulas to real data from quantitative risk management is also pointed out.

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