Summary
In this paper MCMC (Markov Chain Monte Carlo) techniques are proposed to perform Bayesian inference to evaluate the reliability of units with Weibull lifetime, submitted to accelerated and censored life tests. A full Bayesian analysis is done via Gibbs sampling. The marginal posterior of the main parameters and other unobserved quantities of interest derived from them are obtained. Two numerical applications using real and artificially generated data are discussed.
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Acknowledgments
We are grateful to the referees and the editor for helpful comments. The second author would also like to thank the Brazilian research agencies CNPq, Faperj and Ministry of Science and Technology for the continuing support of his research work.
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Mattos, N.M.C., dos Migon, H.S. A Bayesian Analysis of Reliability in Accelerated Life Tests Using Gibbs Sampler. Computational Statistics 16, 299–312 (2001). https://doi.org/10.1007/s001800100066
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DOI: https://doi.org/10.1007/s001800100066