Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6870824 | Computational Statistics & Data Analysis | 2013 | 11 Pages |
Abstract
This paper builds on recent research that focuses on regression modeling of continuous bounded data, such as proportions measured on a continuous scale. Specifically, it deals with beta regression models with mixed effects from a Bayesian approach. We use a suitable parameterization of the beta law in terms of its mean and a precision parameter, and allow both parameters to be modeled through regression structures that may involve fixed and random effects. Specification of prior distributions is discussed, computational implementation via Gibbs sampling is provided, and illustrative examples are presented.
Related Topics
Physical Sciences and Engineering
Computer Science
Computational Theory and Mathematics
Authors
Jorge I. Figueroa-Zúñiga, Reinaldo B. Arellano-Valle, Silvia L.P. Ferrari,