Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
415301 | Computational Statistics & Data Analysis | 2008 | 13 Pages |
Abstract
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-tt, Skew-normal, tt-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.
Related Topics
Physical Sciences and Engineering
Computer Science
Computational Theory and Mathematics
Authors
Alejandro Jara, Fernando Quintana, Ernesto San MartÃn,