Bayesian Two-Sample Prediction with Progressively Type-II Censored Data for Some Lifetime Models

Prediction on the basis of censored data is very important topic in many fields including medical and engineering sciences. In this paper, based on progressive Type-II right censoring scheme, we will discuss Bayesian two-sample prediction. A general form for lifetime model including some well known and useful models such asWeibull and Pareto is considered for obtaining prediction bounds as well as Bayes predictive estimations under squared error loss function for the sth order statistic in a future random sample drawn from the parent population, independently and with an arbitrary progressive censoring scheme. As an illustration, we will present two numerical examples as well as a simulation study to carry out the performance of the procedures obtained.