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Families of $m$-variate distributions with given margins and $m(m-1)/2$ bivariate dependence parameters

Harry Joe
- pp 120-141
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TLDR
In this article, a class of parametric distributions with given margins and m(m? l)/2 dependence parameters, which is based on iteratively mixing conditional distributions, is derived.
Abstract
A class of ra-variate distributions with given margins and m(m ? l)/2 dependence parameters, which is based on iteratively mixing conditional distributions, is derived. The family of multivariate normal distributions is a special case. The motivation for the class is to get parametric families that have m(m ? l)/2 dependence parameters and properties that the family of multivariate normal distributions does not have. Properties of the class are studied, with details for (i) conditions for bivariate tail dependence and non-trivial limiting multivariate extreme value distributions and (ii) range of dependence for a bivariate measure of association such as Kendall's tau.

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Citations
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References
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Book

Inequalities for distributions with given marginals

TL;DR: In this paper, an ordering on discrete bivariate distributions formalizing the notion of concordance is defined and shown to be equivalent to stochastic ordering of distribution functions with identical marginals.
Journal ArticleDOI

Maxima of normal random vectors: between independence and complete dependence

TL;DR: In this paper, the asymptotic dependence structure of bivariate maxima in a triangular array of independent random vectors is analyzed and the analysis of the classical case of i.i.d. random vectors and the known relationship in the Gaussian case is presented.
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