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Beta Regression Models: Joint Mean and Variance Modeling

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Abstract

In this article, joint mean and variance beta regression models are proposed. The proposed models are fitted by applying the Bayesian method and assuming normal prior distribution for the regression parameters. An analysis of synthetic and real data is included, assuming the proposed model, together with a comparison of the result obtained assuming joint modeling of the mean and precision parameters.

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Authors and Affiliations

  1. Departamento de Estadística, Universidad Nacional de Colombia, Carrera 45 # 26-85, Bogotá, Colombia

    Edilberto Cepeda-Cuervo

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  1. Edilberto Cepeda-Cuervo
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Correspondence to Edilberto Cepeda-Cuervo.

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Cepeda-Cuervo, E. Beta Regression Models: Joint Mean and Variance Modeling. J Stat Theory Pract 9, 134–145 (2015). https://doi.org/10.1080/15598608.2014.890983

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  • DOI: https://doi.org/10.1080/15598608.2014.890983

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