Concordance measures for multivariate non-continuous random vectors

Authors:
Mhamed Mesfioui;Jean-François Quessy
Affiliations:
-;-
Venue:
Journal of Multivariate Analysis
Year:
2010

Citing 4
Cited 1

Multivariate concordance

Journal of Multivariate Analysis
Constraints on concordance measures in bivariate discrete data

Journal of Multivariate Analysis
An Introduction to Copulas (Springer Series in Statistics)

An Introduction to Copulas (Springer Series in Statistics)
On rank correlation measures for non-continuous random variables

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On the estimation of Spearman's rho and related tests of independence for possibly discontinuous multivariate data

Journal of Multivariate Analysis

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Abstract

A notion of multivariate concordance suitable for non-continuous random variables is defined and many of its properties are established. This allows the definition of multivariate, non-continuous versions of Kendall's tau, Spearman's rho and Spearman's footrule, which are concordance measures. Since the maximum values of these association measures are not +1 in general, a special attention is given to the computation of upper bounds. The latter turn out to be multivariate generalizations of earlier findings made by Neslehova (2007) [9] and Denuit and Lambert (2005) [2]. They are easy to compute and can be estimated from a data set of (possibly) discontinuous random vectors. Corrected versions are considered as well.