Admissibility of Linear Predictors of Finite Population Parameters under Reflected Normal Loss Function

One of the most important prediction problems in finite population is the prediction of a linear function of characteristic values of a finite population. In this paper the admissibility of linear predictors of an arbitrary linear function of characteristic values in a finite population under reflected normal loss function is considered. Under the super-population model, we obtain the conditions for which the linear predictors are admissible. Also, the risk of some admissible and inadmissible predictors are compared by a simulation study.