A Bayes Sequential Test For The Failure Rate Of An Exponential Distribution With Censored Data
Résumé
This paper provides an optimal sequential decision procedure for deciding between two composite hypotheses about the unknown failure rate of an exponential distribution, using censored data. The procedure has two components, a stopping time and a decision function. The optimal stopping time minimizes the expected total loss due to a wrong decision plus cost of observing the process. The optimal decision function is easily characterized once a stopping time has been specified. A Bayesian approach is used with a gamma prior.
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