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On selection of optimal stochastic model for accelerated life testing

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  • Volf, P.
  • Timková, J.

Abstract

This paper deals with the problem of proper lifetime model selection in the context of statistical reliability analysis. Namely, we consider regression models describing the dependence of failure intensities on a covariate, for instance, a stressor. Testing the model fit is standardly based on the so-called martingale residuals. Their analysis has already been studied by many authors. Nevertheless, the Bayes approach to the problem, in spite of its advantages, is just developing. We shall present the Bayes procedure of estimation in several semi-parametric regression models of failure intensity. Then, our main concern is the Bayes construction of residual processes and goodness-of-fit tests based on them. The method is illustrated with both artificial and real-data examples.

Suggested Citation

  • Volf, P. & Timková, J., 2014. "On selection of optimal stochastic model for accelerated life testing," Reliability Engineering and System Safety, Elsevier, vol. 131(C), pages 291-297.
    • Handle: RePEc:eee:reensy:v:131:y:2014:i:c:p:291-297
    DOI: 10.1016/j.ress.2014.04.015
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    References listed on IDEAS

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    1. Wang, Lizhi & Pan, Rong & Li, Xiaoyang & Jiang, Tongmin, 2013. "A Bayesian reliability evaluation method with integrated accelerated degradation testing and field information," Reliability Engineering and System Safety, Elsevier, vol. 112(C), pages 38-47.
    2. Elsayed, E.A. & Zhang, Hao, 2007. "Design of PH-based accelerated life testing plans under multiple-stress-type," Reliability Engineering and System Safety, Elsevier, vol. 92(3), pages 286-292.
    3. Alan E. Gelfand & Athanasios Kottas, 2003. "Bayesian Semiparametric Regression for Median Residual Life," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 30(4), pages 651-665, December.
    4. René Van Dorp, J. & Mazzuchi, Thomas A., 2005. "A general Bayes weibull inference model for accelerated life testing," Reliability Engineering and System Safety, Elsevier, vol. 90(2), pages 140-147.
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    Cited by:

    1. Cai, Xia & Tian, Yubin & Ning, Wei, 2019. "Change-point analysis of the failure mechanisms based on accelerated life tests," Reliability Engineering and System Safety, Elsevier, vol. 188(C), pages 515-522.

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