A bayesian approach to parameter estimation in simplex regression model: a comparison with beta regression
Some variables are restricted to the open interval (0; 1) and several methodshave been developed to work with them under the scheme of the regressionanalysis. Most of research consider maximum likelihood methods andthe use of Beta or Simplex distributions.This paper presents the use of Bayesian tech...
- Autores:
-
López, Freddy Omar
- Tipo de recurso:
- Article of journal
- Fecha de publicación:
- 2013
- Institución:
- Universidad Nacional de Colombia
- Repositorio:
- Universidad Nacional de Colombia
- Idioma:
- spa
- OAI Identifier:
- oai:repositorio.unal.edu.co:unal/73203
- Acceso en línea:
- https://repositorio.unal.edu.co/handle/unal/73203
http://bdigital.unal.edu.co/37678/
- Palabra clave:
- Beta distribution
Gibbs sampler
Heterogeneous
Proportions
Simplex distribution
Variances
- Rights
- openAccess
- License
- Atribución-NoComercial 4.0 Internacional
| Summary: | Some variables are restricted to the open interval (0; 1) and several methodshave been developed to work with them under the scheme of the regressionanalysis. Most of research consider maximum likelihood methods andthe use of Beta or Simplex distributions.This paper presents the use of Bayesian techniques to estimate the parametersof the simplex regression supported on the implementation of somesimulations and a comparison with Beta regression. We consider both modelswith constant variance and models with |
|---|