Comparison Bayes Estimators of Reliability in the Exponential Distribution

    We produced a study in Estimation for Reliability of the Exponential distribution based on the Bayesian approach. These estimates are derived using Bayesian approaches. In the Bayesian approach, the parameter of the Exponential distribution is assumed to be random variable .we derived bayes estimators of reliability under four types when the prior distribution for the scale parameter of the Exponential distribution is: Inverse Chi-square distribution, Inverted Gamma distribution, improper distribution, Non-informative distribution. And estimators for Reliability is obtained using the well known squared error loss function and weighted squared errors loss function. We used simulation technique, to compare the resultant estimators in terms of their mean squared errors (MSE), mean weighted squared errors (MWSE).Several cases  assumed for the parameter of the exponential distribution for data generating, of different samples sizes (small, medium, and large). The results were obtained by using simulation technique, Programs written using MATLAB-R2008a program were used. In general, Simulation results shown that the resultant estimators in terms of their mean squared errors (MSE) is better than the resultant estimators in terms of their mean weighted squared errors (MWSE).According to the our criteria is the best estimator  that gives the smallest value of MSE or  MWSE .  For example bayes estimation is the best when the prior distribution for the scale parameter is improper and Non-informative distributions  according to the smallest  value  of  MSE  comparative to the values of MWSE  for all samples sizes at some of true value of t and .