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)
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We give a purely probabilistic proof of Sklar's theorem by using a simple continuation technique and sequential arguments. We then consider the case where the distribution function F is unknown but one observes instead a sample of i.i.d. copies distributed according to F: we construct a sequence of copula representers associated with the empirical distribution function of the sample which convergences a.s. to the representer of the copula function associated with F. Eventually, we are surprisingly able to extend the last theorem to the case where the marginals of F are discontinuous.