Exponential inequalities for positively associated random variables and applications.
Exponential inequalities for self-normalized processes with applications.
Exponential inequalities for sums of weakly dependent variables.
Exponential tail bounds for max-recursive sequences.
Extending probability spaces and adapted distribution
Extension of stochastic dominance theory to random variables
Extension of stochastic dominance theory to random variables
In this paper, we develop some stochastic dominance theorems for the location and scale family and linear combinations of random variables and for risk lovers as well as risk averters that extend results in Hadar and Russell (1971) and Tesfatsion (1976). The results are discussed and applied to decision-making.
Extension to copulas and quasi-copulas as special -Lipschitz aggregation operators
Smallest and greatest -Lipschitz aggregation operators with given diagonal section, opposite diagonal section, and with graphs passing through a single point of the unit cube, respectively, are determined. These results are used to find smallest and greatest copulas and quasi-copulas with these properties (provided they exist).
Extremal moment methods and stochastic orders.
Extremal moment methods and stochastic orders. Application in actuarial science.
Extreme distribution functions of copulas
In this paper we study some properties of the distribution function of the random variable C(X,Y) when the copula of the random pair (X,Y) is M (respectively, W) – the copula for which each of X and Y is almost surely an increasing (respectively, decreasing) function of the other –, and C is any copula. We also study the distribution functions of M(X,Y) and W(X,Y) given that the joint distribution function of the random variables X and Y is any copula.