Bayesian estimation of the parameters of the generalized exponential distribution from doubly censored samples

This article deals with the problem of estimating parameters and reliability function of the generalized exponential distribution, based on type II doubly censored sample using Bayesian viewpoints. We also consider the problem of predicting an independent future sample from the same distribution. Importance sampling is used to estimate the parameters, as well as the reliability function, and the Gibbs and Metropolis samplers are used to predict the behavior of future observations from the same distribution.