Estimating the Gumbel-Barnett Copula Parameter of Dependence
Abstract 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,...
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Universidad Nacional de Colombia
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doaj-85ad084a93584268b524201b9a1b0d942020-11-25T03:00:59ZengUniversidad Nacional de Colombia Revista Colombiana de Estadística0120-1751411537310.15446/rce.v41n1.64900S0120-17512018000100053Estimating the Gumbel-Barnett Copula Parameter of DependenceJennyfer Portilla YelaJosé Rafael Tovar CuevasAbstract 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.http://www.scielo.org.co/scielo.php?script=sci_arttext&pid=S0120-17512018000100053&lng=en&tlng=enBayesianCopulaCorrelationDependenceEstimationGB copulaSimulation |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Jennyfer Portilla Yela José Rafael Tovar Cuevas |
spellingShingle |
Jennyfer Portilla Yela José Rafael Tovar Cuevas Estimating the Gumbel-Barnett Copula Parameter of Dependence Revista Colombiana de Estadística Bayesian Copula Correlation Dependence Estimation GB copula Simulation |
author_facet |
Jennyfer Portilla Yela José Rafael Tovar Cuevas |
author_sort |
Jennyfer Portilla Yela |
title |
Estimating the Gumbel-Barnett Copula Parameter of Dependence |
title_short |
Estimating the Gumbel-Barnett Copula Parameter of Dependence |
title_full |
Estimating the Gumbel-Barnett Copula Parameter of Dependence |
title_fullStr |
Estimating the Gumbel-Barnett Copula Parameter of Dependence |
title_full_unstemmed |
Estimating the Gumbel-Barnett Copula Parameter of Dependence |
title_sort |
estimating the gumbel-barnett copula parameter of dependence |
publisher |
Universidad Nacional de Colombia |
series |
Revista Colombiana de Estadística |
issn |
0120-1751 |
description |
Abstract 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. |
topic |
Bayesian Copula Correlation Dependence Estimation GB copula Simulation |
url |
http://www.scielo.org.co/scielo.php?script=sci_arttext&pid=S0120-17512018000100053&lng=en&tlng=en |
work_keys_str_mv |
AT jennyferportillayela estimatingthegumbelbarnettcopulaparameterofdependence AT joserafaeltovarcuevas estimatingthegumbelbarnettcopulaparameterofdependence |
_version_ |
1724695659558207488 |