For a class of skew-normal matrix distributions, the density function, moment generating function and independent conditions are obtained. The noncentral skew Wishart distribution is defined and the necessary and sufficient conditions under which a quadratic form is noncentral skew Wishart distributed random matrix are established. A new version of Cochran’s theorem is given. For illustration, ...

Let {Xn, n ≥ 1} be independent and identically distributed random variables with each Xn following skew normal distribution. Let Mn = max{Xk, 1 ≤ k ≤ n} denote the partial maximum of {Xn, n ≥ 1}. Liao et al. (2014) considered the convergence rate of the distribution of the maxima for random variables obeying the skew normal distribution under linear normalization. In this paper, we obtain the a...

for solving large sparse non-hermitian positive definite linear equations, bai et al. proposed the hermitian and skew-hermitian splitting methods (hss). they recently generalized this technique to the normal and skew-hermitian splitting methods (nss). in this paper, we present an accelerated normal and skew-hermitian splitting methods (anss) which involve two parameters for the nss iteration. w...

Skewness is often present in a wide range of applied problems. One possible approach to model this skewness is based on the class of skew normal distributions. Fitting such distributions remains an inference challenge in various cases. In this paper, we propose and study novel estimators using weighted moments for the closed multivariate skew-normal distribution.

We establish an identity for $$Ef\left( \varvec{Y}\right) - Ef\left( \varvec{X}\right) $$ , when $$\varvec{X}$$ and $$\varvec{Y}$$ both have matrix variate skew-normal distributions the function f satisfies some weak conditions. The characteristic of skew normal distribution is then derived. make use it to derive necessary sufficient conditions comparison under six different orders, such as usu...

Normality of random effects and error terms is a routine assumption for linear effects mixed models. However, such assumption may be unrealistic, obscuring important features of withinand among-unit variation. A simple and robust Bayesian parametric approach that relaxes this assumption by using a multivariate Skew elliptical distributions, which includes the Skew-t, Skew-normal, t-Student, and...

In this paper, we discuss a new generalization of univariate skew-Cauchy distribution with two parameters, we denoted this by GSC(&lambda1, &lambda2), that it has more flexible than the skew-Cauchy distribution (denoted by SC(&lambda)), introduced by Behboodian et al. (2006). Furthermore, we establish some useful properties of this distribution and by two numerical example, show that GSC(&lambd...

The aim of this work is to provide the tools to compute the well-known Kullback–Leibler divergence measure for the flexible family of multivariate skew-normal distributions. In particular, we use the Jeffreys divergence measure to compare the multivariate normal distribution with the skew-multivariate normal distribution, showing that this is equivalent to comparing univariate versions of these...