- Hacettepe Journal of Mathematics and Statistics
- Vol: 51 Issue: 6
- Bayesian estimation of bivariate Pickands dependence function
Bayesian estimation of bivariate Pickands dependence function
Authors : Alireza Ahmadabadi, Gholamhossein Gholami, Burcu Hudaverdi
Pages : 1723-1735
Doi:10.15672/hujms.682730
View : 15 | Download : 6
Publication Date : 2022-12-01
Article Type : Research
Abstract :In the present study, Bayesian method of estimating the Pickands dependence function of bivariate extreme-value copulas is proposed. Initially, cubic B-spline regression is used to model the dependence function. Then, the estimator of Pickands dependence function is obtained by the Bayesian approach. Through the estimation process, the prior and the posterior distributions of the parameter vectors are provided. The posterior sampling algorithm is presented in order to approximate the posterior distribution. We give a simulation study to measure and compare the performance of the proposed Bayesian estimator of the Pickands dependence function. A real data example is also illustrated.Keywords : Bivariate extreme value copula, Pickands dependence function, Bayesian method, reversible jump MCMC