Bayesian Approach for estimating the unknown Scale parameter of Erlang Distribution Based on General Entropy Loss Function

We are used Bayes estimators for unknown scale parameter when shape Parameter is known of Erlang distribution. Assuming different informative priors parameter. derived The posterior density with mean and variance using which the inverse exponential distribution, chi-square Gamma standard Levy distribution as prior. And we based on general entropy loss function (GELF) Simulation method to obtain results. generated cases parameters model, sample sizes. estimates have been compared in terms their mean-squared error (MSE). concluded that best parameterof GELF (c=1,2,3) under gamma prior all samples sizes(n) where true model according smallest values MSE