A generalization of the compound Rayleigh distribution: Using a Bayesian method on cancer survival times

In this paper the generalized compound Rayleigh model exhibiting flexible hazard rate, is high-rated This makes it attractive for modelling survival times of patients showing characteristics of a random hazard rate. The Bayes estimators are derived for the parameters of this model and some survival time parameters from a right censored sample. This is done with respect to conjugate and discrete priors on the parameters of this model under the squared error loss function, Varian's asymmetric linear-exponential (linex) loss function and a weighted linex loss function, The future survival time of a patient is estimated under these loss functions. A Monte Carlo simulation procedure is used where closed form expressions of the estimators cannot be obtained. An example illustrates the proposed estimators for this model.