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Modelling accelerated life test data by using a Bayesian approach

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  • Debajyoti Sinha
  • Kauhsik Patra
  • Dipak K. Dey

Abstract

Summary. Because of the high reliability of many modern products, accelerated life tests are becoming widely used to obtain timely information about their time‐to‐failure distributions. We propose a general class of accelerated life testing models which are motivated by the actual failure process of units from a limited failure population with a positive probability of not failing during the technological lifetime. We demonstrate a Bayesian approach to this problem, using a new class of models with non‐monotone hazard rates, the hazard model with potential scope for use far beyond accelerated life testing. Our methods are illustrated with the modelling and analysis of a data set on lifetimes of printed circuit boards under humidity accelerated life testing.

Suggested Citation

  • Debajyoti Sinha & Kauhsik Patra & Dipak K. Dey, 2003. "Modelling accelerated life test data by using a Bayesian approach," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 52(2), pages 249-259, May.
    • Handle: RePEc:bla:jorssc:v:52:y:2003:i:2:p:249-259
    DOI: 10.1111/1467-9876.00402
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    Cited by:

    1. Burkschat Marco & Kamps Udo & Kateri Maria, 2013. "Estimating scale parameters under an order statistics prior," Statistics & Risk Modeling, De Gruyter, vol. 30(3), pages 205-219, August.
    2. Congdon, Peter, 2006. "A model for non-parametric spatially varying regression effects," Computational Statistics & Data Analysis, Elsevier, vol. 50(2), pages 422-445, January.

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