Bayesian estimation of bivariate Pickands dependence function

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Hacettepe Journal of Mathematics and Statistics
Volume:51 Issue:6
Bayesian estimation of bivariate Pickands dependence function

Bayesian estimation of bivariate Pickands dependence function

Authors : Alireza AHMADABADİ, Gholamhossein GHOLAMİ, Burcu HUDAVERDİ

Pages : 1723-1735

Doi:10.15672/hujms.682730

View : 25 | Download : 7

Publication Date : 2022-12-01

Article Type : Research Paper

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

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