Estimating the Gumbel-Barnett copula parameter of dependence
In this paper, we developed an empirical evaluation of four estimation procedures for the dependence parameter of the Gumbel-Barnett copula obtained from a Gumbel type I distribution. We used the maximum likelihood, moments and Bayesian methods and studied the performance of the estimates, assuming...
- Autores:
-
Portilla Yela, Jennyfer
Tovar Cuevas, José Rafael
- Tipo de recurso:
- Article of journal
- Fecha de publicación:
- 2018
- Institución:
- Universidad Nacional de Colombia
- Repositorio:
- Universidad Nacional de Colombia
- Idioma:
- spa
- OAI Identifier:
- oai:repositorio.unal.edu.co:unal/66493
- Acceso en línea:
- https://repositorio.unal.edu.co/handle/unal/66493
http://bdigital.unal.edu.co/67521/
- Palabra clave:
- 51 Matemáticas / Mathematics
31 Colecciones de estadística general / Statistics
bayesiana
copula Gumbel Barnett
correlación
dependencia copula
estimación
simulación
Copula
Dependence
Correlation
Estimation
Bayesian
Simulation
- Rights
- openAccess
- License
- Atribución-NoComercial 4.0 Internacional
| Summary: | In this paper, we developed an empirical evaluation of four estimation procedures for the dependence parameter of the Gumbel-Barnett copula obtained from a Gumbel type I distribution. We used the maximum likelihood, moments and Bayesian methods and studied the performance of the estimates, assuming three dependence levels and 20 different sample sizes. For each method and scenario, a simulation study was conducted with 1000 runs and the quality of the estimator was evaluated using four different criteria. A Bayesian estimator assuming a Beta(a,b) as prior distribution, showed the best performance regardless the sample size and the dependence structure. |
|---|