A Bayesian interpretation of the multivariate skew-normal distribution

被引：49

作者：

Liseo, B

Loperfido, N

机构：

[1] Univ Roma La Sapienza, Dipartimento Geoecon Linguist Stat & Stor Anal Re, I-0061 Rome, Italy

[2] Univ Urbino, Ist Sci Econ, I-61029 Urbino, Italy

来源：

STATISTICS & PROBABILITY LETTERS | 2003年 / 61卷 / 04期

关键词：

skewness; hierarchical Gaussian models; prior constraints;

D O I：

10.1016/S0167-7152(02)00398-X

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：

This paper provides a unified treatment and a Bayesian interpretation of two different classes of multivariate skew-normal distributions proposed by Azzalini and Dalla Valle (Biometrika 83 (1996) 715) and Gupta et al. (Tech. Rep., Cimat, Mexico (2001)), We show that the above classes of distributions can be viewed as particular cases of a more general family, which naturally arise in constrained modelling, Our approach can be viewed as a direct extension to the multivariate case of the O'Hagan and Leonard (Biometrika 63 (1976) 201) paper, where the authors construct, in the scalar case, a skew prior distribution for the location parameter of a Gaussian random variable, using a simple hierarchical argument. (C) 2002 Elsevier Science B.V. All rights reserved.

引用

页码：395 / 401

页数：7

共 7 条

[1]

Arnold B.C., 2000, SANKHYA A, V62, P23

[2] The multivariate skew-normal distribution [J].