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