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.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.