Sklar's theorem derived using probabilistic continuation and two consistency results

Abstract

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.

Reference

Olivier Faugeras, “Sklar's theorem derived using probabilistic continuation and two consistency results”, Journal of Multivariate Analysis, vol. 122, August 2013, pp. 271–277.