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.
https://hal-utt.archives-ouvertes.fr/hal-02303715
Contributor : Jean-Baptiste Vu Van
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Submitted on : Wednesday, October 2, 2019 - 2:59:29 PM
Last modification on : Thursday, October 3, 2019 - 1:27:37 AM
