Quadratic forms of multivariate skew normal-symmetric distributions

被引:10
|
作者
Huang, WJ [1 ]
Chen, YH [1 ]
机构
[1] NAtl Univ Kaohsiung, Dept Appl Math, Kaohsiung 811, Taiwan
关键词
chi-square distribution; independence; moment generating function; non-normal models; quadratic form; skew normal distribution; skew symmetric distribution;
D O I
10.1016/j.spl.2005.10.018
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
Following the paper by Gupta and Chang (Multivariate skew-symmetric distributions. Appl. Math. Lett. 16, 643-646 2003.) we generate a multivariate skew normal-symmetric distribution with probability density function of the form f(z)(z) = 2 phi(p)(z; Omega)G(alpha'z), where Omega > 0, alpha is an element of R-rho, phi(p)(z;.Omega) is the p-dimensional normal p.d.f. with zero mean vector and correlation matrix Omega, and G is taken to be an absolutely continuous function such that G' is symmetric about 0. First we obtain the moment generating function of certain quadratic forms. It is interesting to find that the distributions of some quadratic forms are independent of G. Then the joint moment generating functions of a linear compound and a quadratic form, and two quadratic forms, and conditions for their independence are given. Finally we take G to be one of normal, Laplace, logistic or uniform distribution, and determine the distribution of a special quadratic form for each case. (C) 2005 Elsevier B.V. All rights reserved.
引用
收藏
页码:871 / 879
页数:9
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