Antedependence Models for Skewed Continuous Longitudinal Data
Author | : Shu-Ching Chang |
Publisher | : |
Total Pages | : 141 |
Release | : 2013 |
ISBN-10 | : OCLC:860985635 |
ISBN-13 | : |
Rating | : 4/5 (35 Downloads) |
Download or read book Antedependence Models for Skewed Continuous Longitudinal Data written by Shu-Ching Chang and published by . This book was released on 2013 with total page 141 pages. Available in PDF, EPUB and Kindle. Book excerpt: Since the class of skew normal random variables is closed under the addition of independent standard normal random variables, we then consider an autoregressively characterized PAC model with a combination of independent skew normal and normal innovations. Explicit expressions for the marginals, which all have skew normal distributions, and maximum likelihood estimates of model parameters, are given. Numerical results show that these three proposed models may provide reasonable fits to some continuous non-Gaussian longitudinal data sets. Furthermore, we compare the fits of these models to the Treatment A cattle growth data using penalized likelihood criteria, and demonstrate that the AD(2) multivariate skew normal model fits the data best among those proposed models.