Bayes' Estimators for the Mean of Rayleigh Distribution with Different Priors


In this paper Bayes' estimators for the mean of Rayleigh distribution with three different prior information's are presented under the squared error loss function. Jeffrey, extension of Jeffrey and inverted Gamma prior information's are considered. A comparison was made through a Monte Carlo simulation study. The comparison was made on the performance of these estimators with respect to the mean square error (MSE) and the mean percentage error (MPE). The results of comparison by MSE and MPEshowed that the Bayes' estimator of the mean with inverted Gamma prior was the best followed by Jeffrey prior estimator. While comparison by MPE showed better results than MSE.