This paper generalizes Stein's Lemma recently obtained for elliptical class distributions to the generalized skew-elliptical family of distributions. Stein's Lemma provides a useful tool for deriving covariances between functions of component random variables. This Lemma has applications in finance, notably for portfolio selection and hence for the capital asset pricing model (CAPM), as well as technical applications such as the computation of moments. It also leads to important propositions concerning the mean and variance of generalized skew-elliptical variables
AbstractIn this paper, a family of the skew elliptical distributions is defined and investigated. So...
AbstractIn a subclass of elliptical distributions, Stein estimators are robust in estimating the mea...
Singular matrix variate skew-elliptical distribution and the distribution of general linear transfor...
AbstractFor the family of multivariate normal distribution functions, Stein's Lemma presents a usefu...
For the family of multivariate normal distribution functions, Stein's Lemma presents a useful tool f...
Inspired by the work of Adcock, Landsman, and Shushi (2019) which established the Stein’s lemma for ...
When two random variables have a bivariate normal distribution, Stein's lemma (Stein, 1973, 1981), p...
This paper introduces generalized skew-elliptical distributions (GSE), which include the multivari...
This paper introduces generalized skew-elliptical distributions (GSE), which include the multivaria...
Abstract This paper introduces generalized skew-elliptical distributions (GSE), which include the mu...
Linear functions of order statistics from bivariate, exchangeable, continuous and elliptical random ...
The univariate and multivariate skew-normal distributions have a number of intriguing properties. It...
In this paper, we derive the Stein-Haff identity for the multivariate elliptically contoured matrix ...
The thesis recalls the traditional theory of elliptically symmetric distributions. Their basic prope...
In this paper, we present a minimal formalism for Stein operators which leads to different probabili...
AbstractIn this paper, a family of the skew elliptical distributions is defined and investigated. So...
AbstractIn a subclass of elliptical distributions, Stein estimators are robust in estimating the mea...
Singular matrix variate skew-elliptical distribution and the distribution of general linear transfor...
AbstractFor the family of multivariate normal distribution functions, Stein's Lemma presents a usefu...
For the family of multivariate normal distribution functions, Stein's Lemma presents a useful tool f...
Inspired by the work of Adcock, Landsman, and Shushi (2019) which established the Stein’s lemma for ...
When two random variables have a bivariate normal distribution, Stein's lemma (Stein, 1973, 1981), p...
This paper introduces generalized skew-elliptical distributions (GSE), which include the multivari...
This paper introduces generalized skew-elliptical distributions (GSE), which include the multivaria...
Abstract This paper introduces generalized skew-elliptical distributions (GSE), which include the mu...
Linear functions of order statistics from bivariate, exchangeable, continuous and elliptical random ...
The univariate and multivariate skew-normal distributions have a number of intriguing properties. It...
In this paper, we derive the Stein-Haff identity for the multivariate elliptically contoured matrix ...
The thesis recalls the traditional theory of elliptically symmetric distributions. Their basic prope...
In this paper, we present a minimal formalism for Stein operators which leads to different probabili...
AbstractIn this paper, a family of the skew elliptical distributions is defined and investigated. So...
AbstractIn a subclass of elliptical distributions, Stein estimators are robust in estimating the mea...
Singular matrix variate skew-elliptical distribution and the distribution of general linear transfor...