Bayesian estimation of bivariate Pickands dependence function

Ahmadabadi A., Gholami G., Hüdaverdi B.

Hacettepe Journal of Mathematics and Statistics, cilt.51, sa.6, ss.1723-1735, 2022 (SCI-Expanded) identifier identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 51 Sayı: 6
  • Basım Tarihi: 2022
  • Doi Numarası: 10.15672/hujms.682730
  • Dergi Adı: Hacettepe Journal of Mathematics and Statistics
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, zbMATH, TR DİZİN (ULAKBİM)
  • Sayfa Sayıları: ss.1723-1735
  • Anahtar Kelimeler: Bivariate extreme value copula, Pickands dependence function, Bayesian method, reversible jump MCMC
  • Dokuz Eylül Üniversitesi Adresli: Evet

Özet

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.