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

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  • S. M. T. K. MirMostafaee
  • Morteza Amini
  • A. Asgharzadeh

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.

Suggested Citation

  • S. M. T. K. MirMostafaee & Morteza Amini & A. Asgharzadeh, 2017. "Bayesian prediction of minimal repair times of a series system based on hybrid censored sample of components’ lifetimes under Rayleigh distribution," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 46(4), pages 1788-1806, February.
    • Handle: RePEc:taf:lstaxx:v:46:y:2017:i:4:p:1788-1806
    DOI: 10.1080/03610926.2015.1030418
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