estimation and prediction from progressively censored data using proportional hazards model

In this paper‎, ‎based on progressively type-ii censored samples‎, ‎the maximum likelihood and bayes estimators are derived for some lifetime parameters‎. ‎ ‎in the bayesian framework‎, ‎the point estimations of unknown parameters under both symmetric and asymmetric loss functions are discussed‎. ‎the bayesian estimations have been obtained using the conjugate prior and discrete priors for the shape and scale parameters‎, ‎respectively‎. ‎we also provide bayes prediction intervals for the times to failure of units censored in multiple stages in a progressively censored sample‎. ‎finally‎, ‎two numerical examples are presented to illustrate the results.