WinBugs CODE for Beta Regression Models

In this paper WinBugs code to fit joint mean and precision (variance) beta regression models is presented. These models are fitted applying Bayesian methodology and assuming normal prior distribution for the regression parameters. Analysis of structural data are included, assuming these models.

Autores:
Cepeda Cuervo, Edilberto
Tipo de recurso:
Work document
Fecha de publicación:
2019
Institución:
Universidad Nacional de Colombia
Repositorio:
Universidad Nacional de Colombia
Idioma:
spa
OAI Identifier:
oai:repositorio.unal.edu.co:unal/9659
Acceso en línea:
https://repositorio.unal.edu.co/handle/unal/9659
http://bdigital.unal.edu.co/6610/
Palabra clave:
31 Colecciones de estadística general / Statistics
51 Matemáticas / Mathematics
Beta regression models, WinBugs CODE, Bayesian methodology
Rights
openAccess
License
Atribución-NoComercial 4.0 Internacional
Description
Summary:In this paper WinBugs code to fit joint mean and precision (variance) beta regression models is presented. These models are fitted applying Bayesian methodology and assuming normal prior distribution for the regression parameters. Analysis of structural data are included, assuming these models.