Bayesian prediction of k-record values based on progressively censored data from exponential distribution

Abstract

In this paper, based on a progressively Type-II right censored sample, we discuss the prediction of k-record values from a future sequence. By considering the parent distribution as exponential, we derive Bayesian prediction intervals as well as Bayesian point predictors for k-record values from a future sequence based on an observed progressively Type-II right censored sample. The corresponding results for ordinary Type-II censored sample and the usual order statistics are then deduced as special cases. A real data set concerning the breakdown times of an insulating fluid in an accelerated life-test is used for illustrating all the results developed here.

Keywords:

• highest posterior density
• interval prediction
• point prediction
• predictive density
• progressive Type-II right censoring
• record values
• k-records

Acknowledgements

The authors thank the associate editor and the referees for their constructive comments and useful suggestions on the original version of this manuscript, which led to this improved version.