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Computational Statistics

, Volume 16, Issue 2, pp 299–312 | Cite as

A Bayesian Analysis of Reliability in Accelerated Life Tests Using Gibbs Sampler

  • Néli Maria Costa Mattos
  • Hélio Santos dos Migon
Article

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.

Keywords

Bayesian analysis Gibbs sampler Reliability Accelerated life tests Weibull distribution 

Notes

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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Copyright information

© Physica-Verlag 2001

Authors and Affiliations

  • Néli Maria Costa Mattos
    • 1
  • Hélio Santos dos Migon
    • 2
  1. 1.Departamento de Engenharia de SistemasInstitute Militar de EngenhariaRio de JaneiroBrazil
  2. 2.Institute de Matemática & COPPEUniversidade Federal do Rio de JaneiroRio de JaneiroBrazil

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