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Revista Colombiana de Estadística
versión impresa ISSN 0120-1751
Resumen
CORRALES-BOSSIO, Martha Lucía y CEPEDA-CUERVO, Edilberto. A Bayesian Approach to Mixed Gamma Regression Models. Rev.Colomb.Estad. [online]. 2019, vol.42, n.1, pp.81-99. Epub 23-Mayo-2019. ISSN 0120-1751. https://doi.org/10.15446/rce.v42n1.69334.
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.
Palabras clave : Bayesian analysis; Gamma distribution; Gamma regression; Mixed models.