Bayesian prediction based on type-I censored data from a mixture of Burr type XII distribution and its reciprocal

Abstract

This paper is concerned with the problem of obtaining Bayesian prediction bounds of future observables from a finite mixture of Burr type XII distribution with its reciprocal based on type-I censored data. We consider the one-sample and two-sample prediction schemes using the Markov chain Monte Carlo algorithm. Numerical examples are given to illustrate the procedures and the accuracy of prediction intervals is investigated via extensive Monte Carlo simulation.

Keywords:

• mixture of Burr type XII and its reciprocal
• type-I censoring
• one- and two-sample predictions
• Markov chain Monte Carlo

Acknowledgements

The authors would like to thank the referee for his helpful remarks which improved the original manuscript.