Shape mixtures of multivariate skew-normal distributions

被引：32

作者：

Arellano-Valle, Reinaldo B. ^{[2
]}

Genton, Marc G. ^{[1
,3
]}

Loschi, Rosangela H. ^{[4
]}

机构：

[1] Univ Geneva, Dept Econometr, CH-1211 Geneva 4, Switzerland

[2] Pontificia Univ Catolica Chile, Fac Matemat, Santiago 32, Chile

[3] Texas A&M Univ, Dept Stat, College Stn, TX 77843 USA

[4] Univ Fed Minas Gerais, Dept Estatist, BR-31270901 Belo Horizonte, MG, Brazil

来源：

JOURNAL OF MULTIVARIATE ANALYSIS | 2009年 / 100卷 / 01期

基金：

瑞士国家科学基金会;

关键词：

Bayes; Conjugacy; Shape parameter; Skewness; Skew-normal distribution; Regression model; Robustness;

D O I：

10.1016/j.jmva.2008.03.009

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：

Classes of shape mixtures of independent and dependent multivariate skew-normal distributions are considered and some of their main properties are studied. If interpreted from a Bayesian point of view, the results obtained in this paper bring tractability to the problem of inference for the shape parameter, that is, the posterior distribution can be written in analytic form. Robust inference for location and scale parameters is also obtained under particular conditions. (C) 2008 Elsevier Inc. All rights reserved.

引用

页码：91 / 101

页数：11

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