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Bayesian Analysis of the Brown–Proschan Model

Author

Listed:
  • Nguyen Dinh Tuan

    (Université de Technologie de Troyes, 12 rue Marie Curie, CS 42060, 10004 Troyes cedex, France)

  • Dijoux Yann

    (Université de Technologie de Troyes, 12 rue Marie Curie, CS 42060, 10004 Troyes cedex, France)

  • Fouladirad Mitra

    (Université de Technologie de Troyes, 12 rue Marie Curie, CS 42060, 10004 Troyes cedex, France)

Abstract

The paper presents a Bayesian approach of the Brown–Proschan imperfect maintenance model. The initial failure rate is assumed to follow a Weibull distribution. A discussion of the choice of informative and non-informative prior distributions is provided. The implementation of the posterior distributions requires the Metropolis-within-Gibbs algorithm. A study on the quality of the estimators of the model obtained from Bayesian and frequentist inference is proposed. An application to real data is finally developed.

Suggested Citation

  • Nguyen Dinh Tuan & Dijoux Yann & Fouladirad Mitra, 2015. "Bayesian Analysis of the Brown–Proschan Model," Stochastics and Quality Control, De Gruyter, vol. 30(1), pages 9-20, June.
    • Handle: RePEc:bpj:ecqcon:v:30:y:2015:i:1:p:9-20:n:2
    DOI: 10.1515/eqc-2015-6002
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    References listed on IDEAS

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    1. Guida, Maurizio & Pulcini, Gianpaolo, 2006. "Bayesian analysis of repairable systems showing a bounded failure intensity," Reliability Engineering and System Safety, Elsevier, vol. 91(7), pages 828-838.
    2. Guo R. & Ascher H. & Love E., 2001. "Towards Practical and Synthetical Modelling of Repairable Systems," Stochastics and Quality Control, De Gruyter, vol. 16(1), pages 147-182, January.
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