Linear mixed models with skew-elliptical distributions:: A Bayesian approach

被引:85
作者
Jara, Alejandro [1 ]
Quintana, Fernando [2 ]
Martin, Ernesto San [2 ,3 ]
机构
[1] Catholic Univ Louvain, Ctr Biostat, B-3000 Louvain, Belgium
[2] Pontificia Univ Catolica Chile, Dept Stat, Santiago, Chile
[3] Pontificia Univ Catolica Chile, Measurement Ctr MIDE UC, Santiago, Chile
关键词
D O I
10.1016/j.csda.2008.04.027
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Normality of random effects and error terms is a routine assumption for linear mixed models. However, such an assumption may be unrealistic, obscuring important features of within- and among-unit variation. A simple and robust Bayesian parametric approach that relaxes this assumption by using a multivariate skew-elliptical distribution, which includes the Skew-t, Skew-normal, t-Student, and Normal distributions as special cases and provides flexibility in capturing a broad range of non-normal and asymmetric behavior is presented. An appropriate posterior simulation scheme is developed and the methods are illustrated with an application to a longitudinal data example. (C) 2008 Elsevier B.V. All rights reserved.
引用
收藏
页码:5033 / 5045
页数:13
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