Bayesian inference of a dependent competing risk data

Recently, Feizjavadian and Hashemi (Analysis of dependent competing risks in presence progressive hybrid censoring using Marshall–Olkin bivariate Weibull distribution. Comput Stat Data Anal. 2015;82:19–34) provided a classical inference data set distribution when the failure an unit at particular time point can happen due to more than one cause. The aim this paper is provide Bayesian analysis same model based on very flexible Gamma–Dirichlet (GD) prior scale parameters. has certain advantages over case. We Bayes estimates unknown parameters associated highest posterior density credible intervals Gibbs sampling technique. further consider assuming partially ordered GD cause severe other have extended results for different schemes also.