Modelling accelerated life test data by using a Bayesian approach |
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Authors: | Debajyoti Sinha Kauhsik Patra Dipak K. Dey |
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Affiliation: | Medical University of South Carolina, Charleston, USA ; Harvard School of Public Health, Boston, USA ; University of Connecticut, Storrs, USA |
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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. |
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Keywords: | Conditional predictive ordinate Latent risk Limited failure population Markov chain Monte Carlo methods |
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