Abstract:
The inverse Gaussian distribution has been found to be a useful model for those situations wherever early failure or occurrences dominate the lifetime distribution. Suppose that components are put on life test and that their lifetimes have an inverse Gaussian distribution. Prediction bounds are derived for unobserved sample components using Bayesian and non-Bayesian approaches. Equations are obtained from which the prediction bounds may be calculated. Some numerical examples are presented
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