In this paper, the Bayesian analysis of the survival data arising from a Rayleigh model is carried out under the assumption that the clinical study based on n patients is terminated at the dth death, for some preassigned d (0 < d = n), resulting in the survival times t1 = t2 = ... = td, and (n - d) survivors. For the prior knowledge about the Rayleigh parameter, the gamma density, the inverted gamma density, and the beta density of the second kind are respectively assumed, and for each of these prior densities, the Bayes estimators of the mean survival time, the hazard function, and the survival function are obtained by assuming the usual squared error loss function. Finally, the analysis is extended to situations wherein the exact survival time is not available for any patient but only the deaths in given time intervals are recorded. The computations are illustrated by a numerical example
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