Bayes Estimation under Balanced Loss Functions

In this research, the researcher has derived different standard Bayes estimators for scale parameter of Exponential distribution by using balanced and unbalanced loss function. This estimation includes two cases availability and lack of primary information (Jeffery and Gamma conjugate priors) about the phenomenon studied. Simulation experiments with different sample sizes and virtual parameters have been built for this purpose, then a comparison is mads between these estimators depend on the Mean Square Error (MSE) criteria. The results have demonstrating the superiority of balanced loss functions in the absence of prior information about the phenomenon studied, while they may not have the same efficiency if availability of prior information about this phenomenon is cannot found.