The Annals of Statistics

Multivariate Archimedean copulas, d-monotone functions and 1-norm symmetric distributions

Alexander J. McNeil and Johanna Nešlehová

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It is shown that a necessary and sufficient condition for an Archimedean copula generator to generate a d-dimensional copula is that the generator is a d-monotone function. The class of d-dimensional Archimedean copulas is shown to coincide with the class of survival copulas of d-dimensional 1-norm symmetric distributions that place no point mass at the origin. The d-monotone Archimedean copula generators may be characterized using a little-known integral transform of Williamson [Duke Math. J. 23 (1956) 189–207] in an analogous manner to the well-known Bernstein–Widder characterization of completely monotone generators in terms of the Laplace transform. These insights allow the construction of new Archimedean copula families and provide a general solution to the problem of sampling multivariate Archimedean copulas. They also yield useful expressions for the d-dimensional Kendall function and Kendall’s rank correlation coefficients and facilitate the derivation of results on the existence of densities and the description of singular components for Archimedean copulas. The existence of a sharp lower bound for Archimedean copulas with respect to the positive lower orthant dependence ordering is shown.

Article information

Ann. Statist. Volume 37, Number 5B (2009), 3059-3097.

First available in Project Euclid: 17 July 2009

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Zentralblatt MATH identifier

Primary: 62E10: Characterization and structure theory 62H05: Characterization and structure theory 62H20: Measures of association (correlation, canonical correlation, etc.)
Secondary: 60E05: Distributions: general theory

Archimedean copula d-monotone function dependence ordering frailty model ℓ_1-norm symmetric distribution Laplace transform stochastic simulation Williamson d-transform


McNeil, Alexander J.; Nešlehová, Johanna. Multivariate Archimedean copulas, d -monotone functions and ℓ 1 -norm symmetric distributions. Ann. Statist. 37 (2009), no. 5B, 3059--3097. doi:10.1214/07-AOS556.

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