Copulas and vines allow us to model the distribution of multivariate random variables in a flexible way. This article introduces copulas via Sklar’s theorem, explains how pair copula constructions are built by decomposing multivariate copula densities and illustrates vine graphical representations.

We show that the lower and upper Frechét-Hoeffding copulas, which are singular, can be regularized to absolutely continuous copulas. The method, which is constructive and explicit, states sufficient conditions for when an absolutely continuous copula can be achieved by averaging. A higher degree of regularisation cannot be achieved with the proposed method.

We state a multidimensional Functional Central Limit Theorem for weakly dependent random vectors. We apply this result to copulas. We get the weak convergence of the empirical copula process and of its smoothed version. The finite dimensional convergence of smoothed copula densities is also proved. A new definition and the theoretical analysis of conditional copulas and their empirical counterp...

there are several theorical results about order statistics and copulas in the literature that have  been mentioned also by nelsen cite{p20}. the present study after reviewing some of these results, relies on  simulation technique to investigate the mentioned results about order statistics and copulas. the study concentrates on two well known archimedean gumbel and frank families in the case tha...

We introduce a constructive method, by using a doubly stochastic measure, to describe all the copulas that, in view of Sklar’s Theorem, are able to connect a bivariate distribution to its marginals. We use this to give the lower and upper optimal bounds for all the copulas that extend a given subcopula.

When the failure function is monotone, some monotonic reliability methods are used to gratefully simplify and facilitate the reliability computations. However, these methods often work in a transformed iso-probabilistic space. To this end, a monotonic simulator or transformation is needed in order that the transformed failure function is still monotone. This note proves at first that the output...

In order to study copula families that have different tail patterns and tail asymmetry than multivariate Gaussian and t copulas, we introduce the concepts of tail order and tail order functions. These provide an integrated way to study both tail dependence and intermediate tail dependence. Some fundamental properties of tail order and tail order functions are obtained. For the multivariate Arch...

Lévy processes and infinitely divisible distributions are increasingly defined in terms of their Lévy measure. In order to describe the dependence structure of a multivariate Lévy measure, Tankov (2003) introduced positive Lévy copulas. Together with the marginal Lévy measures they completely describe multivariate Lévy measures on R+ . In this paper, we show that any such Lévy copula defines it...

Goodness-of-Fit Testing for Copula-based models with Applications in Atmospheric Science by Albert Rapp The University of Wisconsin–Milwaukee, 2017 Under the Supervision of Professor Vincent E. Larson Every elementary probability course discusses how to construct joint distribution functions of independent random variables but joint distribution functions of dependent random variables are usual...