Bayes Estimators for the Reliability Function of Pareto Type I Distribution Under Squared-Log Error Loss Function

Abstract

In this paper we obtained Basyian estimators of the reliability function of the Pareto type I distribution under Squared-Log error loss function. In order to get better understanding of our Bayesian analysis we consider non-informative prior for the shape parameter Using Jeffery prior Information as well as informative prior density represented by Exponential distribution. The Bayes estimator of the reliability function of the Pareto type I distribution under Squared-Log error loss function is compared with Some classical estimators such as, the Maximum Likelihood Estimator (MLE), the Uniformly Minimum Variance Unbiased Estimator (UMVUE), and the Minimum Mean Squared Error (MinMSE) estimator according to Monte-Carlo simulation study. The performance of these estimators is compared depending on the Integrated mean squared errors (IMSE’s).