Abstract:
In this paper we consider the estimators of the variance, \theta^{2} of the 2-parameter exponential distribution. The variance estimators consist of the minimum mean squared error estimator and a class of shrinkage estimators given prior information. The purpose of this study is to present a theorem that compares these estimators based on the Multiple Criteria Decision Making method. The results show that \hat{\theta}_{2(-1)}^{2} is the best estimator while \hat{\theta}_{2(2)}^{2}, \hat{\theta}_{2(1)}^{2}, \hat{\theta}_{2MMSE}^{2} and \hat{\theta}_{2(-2)}^{2} are lower in rank respectively when sample size is greater than ten.