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Revista Colombiana de Estadística
Print version ISSN 0120-1751
Rev.Colomb.Estad. vol.42 no.1 Bogotá Jan./June 2019 Epub May 23, 2019
https://doi.org/10.15446/rce.v42n1.69334
Artículos originales de investigación
A Bayesian Approach to Mixed Gamma Regression Models
Un enfoque bayesiano para modelos mixtos de regresión Gamma
a Escuela de Matemáticas, Universidad Sergio Arboleda, Bogotá, Colombia. martha.corrales@usa.edu.co
b Departamento de Estadística, Facultad de Ciencias, Universidad Nacional de Colombia, Bogotá, Colombia. ecepedac@unal.edu.co
Gamma regression models are a suitable choice to model continuous variables that take positive real values. This paper presents a gamma regression model with mixed effects from a Bayesian approach. We use the parametrization of the gamma distribution in terms of the mean and the shape parameter, both of which are modelled through regression structures that may involve fixed and random effects. A computational implementation via Gibbs sampling is provided and illustrative examples (simulated and real data) are presented.
Key words: Bayesian analysis; Gamma distribution; Gamma regression; Mixed models
Los modelos de regresión gamma son una opción adecuada para modelar variables continuas que toman valores reales positivos. Este artículo presenta un modelo de regresión gamma con efectos mixtos desde un enfoque bayesiano. Utilizamos la parametrización de la distribución gamma en términos de la media y el parámetro de forma, los cuales se modelan a través de estructuras de regresión que pueden involucrar efectos fijos y aleatorios. Se proporciona una implementación computacional a través del muestreo de Gibbs y se presentan ejemplos ilustrativos (datos simulados y reales).
Palabras clave: Análisis bayesiano; Distribución Gamma; Regresión Gamma; Modelos mixtos
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Received: December 2017; Accepted: November 2018
This is an open-access article distributed under the terms of the Creative Commons Attribution License
