The fundamental best-possible bounds inequality for bivariate distribution functions with given margins is the Frechet-Hoeffding inequality: If H denotes the joint distribution function of random variables X and Y whose margins are F and G, respectively, then...

We characterize the class of binary operations \/o on distribution functions which are both induced pointwise, in the sense that the value of \/o(F, G) at g is a function of F(t) and G(t) (e.g. mixtures), and derivable from functions on random variables (e.g. convolution).

If X and Y are continuous random variables with joint distribution function H, then the Kendall distribution function of (X,Y) is the distribution function of the random variable H(X,Y). Kendall distribution functions arise in the study of stochastic orderings of random vectors. In this paper we...

We discuss a two-dimensional analog of the probability integral transform for bivariate distribution functions H1 and H2, i.e., the distribution function of the random variable H1(X,Y) given that the joint distribution function of the random variables X and Y is H2. We study the case when H1 and...

We investigate some properties of the partially ordered sets of multivariate copulas and quasi-copulas. Whereas the set of bivariate quasi-copulas is a complete lattice, which is order-isomorphic to the Dedekind-MacNeille completion of the set of bivariate copulas, we show that this is not the...

We study a method, which we call a copula (or quasi-copula) diagonal splice, for creating new functions by joining portions of two copulas (or quasi-copulas) with a common diagonal section. The diagonal splice of two quasi-copulas is always a quasi-copula, and we find a necessary and sufficient...

We show that Spearman's rho is a measure of average positive (and negative) quadrant dependence, and that Kendall's tau is a measure of average total positivity (and reverse regularity) of order two.

This paper studies the problem of finding best-possible upper bounds on the Value-at-Risk for a function of two random variables when the marginal distributions are known and additional nonparametric information on the dependence structure, such as the value of a measure of association, is...