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Bayesian analysis of discrete time warranty data
Authors:David Stephens   Martin Crowder
Affiliation:Imperial College, London, UK.
Abstract:Summary.  The analysis of warranty claim data, and their use for prediction, has been a topic of active research in recent years. Field data comprising numbers of units returned under guarantee are examined, covering both situations in which the ages of the failed units are known and in which they are not. The latter case poses particular computational problems for likelihood-based methods because of the large number of feasible failure patterns that must be included as contributions to the likelihood function. For prediction of future warranty exposure, which is of central concern to the manufacturer, the Bayesian approach is adopted. For this, Markov chain Monte Carlo methodology is developed.
Keywords:Data augmentation    Discrete–continuous Markov chain Monte Carlo methodology    Guarantee exposure    Marginal counts    Non-repairable failure    Product reliability    Warranty
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