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.

Keywords:

Bayes estimation , Maximum likelihood estimation , Prediction intervals , Progressively censored samples , Proportional hazard model