Statistical prediction analysis plays an important role in various fields including medical and engineering sciences. In this paper, based on progressively Type-II right censored data, we shall consider Bayesian two-sample prediction. Generalized exponential (GE) model, which has been introduced as a quite effective model for lifetime data analysis instead of the Weibull or gamma distributions, is considered for obtaining prediction bounds for the s-th order statistic in a future random sample drawn independently and with different and arbitrary progressive censoring schemes. Finally, we carry out a simulation study to assess the computational comparison of coverage probabilities in different progressive Type-II censoring schemes based on Bayesian two-sample prediction. In addition, we present schemes which are not suitable for predicting the s-th order statistic in a future random sample drawn from GE model.

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