Bayesian Prediction for Progressive Censored Data From the Weibull-Geometric Model

SYNOPTIC ABSRACT

This article is concerned with the problem of predicting future observables from the Weibull-geometric model based on progressively Type-II censored data. The Bayes point predictors and the Bayesian prediction intervals are obtained. The one and two-sample prediction techniques are considered. Numerical computations are given to illustrate the performance of the procedures.

KEY WORDS AND PHRASES:

• Weibull-geometric distribution
• progressively censored data
• Bayesian prediction
• one and two-samples techniques

Acknowledgment

The authors would like to thank the associate editor and the referees for their valuable remarks and comments that improved the original manuscript.