Beta Regression Models: Joint Mean and Variance Modeling
In this paper joint mean and variance beta regression models are proposed. The proposed models are fitted applying Bayesian methodology and assuming normal prior distribution for the regression parameters. An analysis of structural and real data is included, assuming the proposed model, together wit...
- Autores:
-
Cepeda Cuervo, Edilberto
- Tipo de recurso:
- Work document
- Fecha de publicación:
- 2015
- Institución:
- Universidad Nacional de Colombia
- Repositorio:
- Universidad Nacional de Colombia
- Idioma:
- spa
- OAI Identifier:
- oai:repositorio.unal.edu.co:unal/9323
- Palabra clave:
- 31 Colecciones de estadística general / Statistics
Beta regression
Bayesian methodology
mean and variance modeling
- Rights
- openAccess
- License
- Atribución-NoComercial 4.0 Internacional
| Summary: | In this paper joint mean and variance beta regression models are proposed. The proposed models are fitted applying Bayesian methodology and assuming normal prior distribution for the regression parameters. An analysis of structural 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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