Objective Bayesian analysis for bivariate Marshall–Olkin exponential distribution

Abstract

The Bayesian estimators for the unknown parameters of the bivariate Marshall–Olkin exponential distribution under noninformative priors have been considered and several reference priors have been derived. A class of priors is found by matching the coverage probability of one-side Bayesian credible intervals with the corresponding frequentist coverage probabilities. It is noted that some of the reference priors are also matching priors and the posterior distributions based on the reference priors and matching priors are proper. Closed forms of Bayesian estimators are obtained with respect to the quadratic loss function. Gibbs sampling is utilized to obtain the credible intervals and coverage probabilities of parameters. Comparisons in the efficiency of the maximum likelihood estimators and Bayesian estimators under different reference priors and matching priors for various sample sizes have been done by Monte Carlo simulations. A real data set is analyzed for illustrative purpose.