Abstract
Based on a progressively Type-II censored sample, Bayesian estimation of the parameters as well as Bayesian prediction of the unobserved failure times from the generalized exponential (GE) distribution are studied. Importance sampling is used to estimate the scale and shape parameters. The Gibbs and Metropolis samplers are considered for predicting times to failure of units in multiple stages. A numerical simulation study involving three data sets is presented to illustrate the methods of estimation and prediction.