Gamma regression models with the Gammareg R package
The class of gamma regression models is based on the assumption that the dependent variable is gamma distributed and that its mean is related to a set of regressors through a linear predictor with unknown coefficients and a link function. This link can be the identity, the inverse or the logarithm f...
- Autores:
-
Cepeda-Cuervo, Edilberto
Corrales-Bosio, Martha
- 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/21593
- Acceso en línea:
- https://repositorio.unal.edu.co/handle/unal/21593
http://bdigital.unal.edu.co/12542/
- Palabra clave:
- 31 Colecciones de estadística general / Statistics
Gamma regression
Mean regression structures
Shape regression structures
Fisher Scoring algorithm
R-package
- Rights
- openAccess
- License
- Atribución-NoComercial 4.0 Internacional
| Summary: | The class of gamma regression models is based on the assumption that the dependent variable is gamma distributed and that its mean is related to a set of regressors through a linear predictor with unknown coefficients and a link function. This link can be the identity, the inverse or the logarithm function. The model also includes a shape parameter, which may be constant or dependent on a set of regressors through a link function, as the logarithm function. In this paper we describe the Gammareg Rpackage, which provides the class of gamma regressions in the R system for their statistical computing. The underlying theory is briefly presented and the library implementation illustrated from simulation studies. |
|---|