Bayesian prediction of minimal repair times of a series system based on hybrid censored sample of components’ lifetimes under Rayleigh distribution

ABSTRACT

In this paper, we develop Bayesian predictive inferential procedures for prediction of repair times of a series system, applying a minimal repair strategy, using the information contained in an independent observed hybrid censored sample of the lifetimes of the components of the system, assuming the underlying distribution of the lifetimes to be Rayleigh distribution. An illustrative real data example and a simulation study are presented for the purpose of illustration and comparison of the proposed predictors.

KEYWORDS:

• Bayesian interval prediction
• Bayesian point prediction
• coherent systems
• highest posterior density
• reliability

MATHEMATICS SUBJECT CLASSIFICATION:

• 62F15
• 65C60

Acknowledgments

We would like to thank the associate editor and the anonymous referees for their valuable comments and suggestions on an earlier version of this manuscript, which resulted in this improved version. We also thank Prof. N. Balakrishnan for his useful comments. This paper has been supported financially by a grant by University of Mazandaran and Iran’s National Elites Foundation.