Exponential Type Estimators of Finite Population Mean in Stratified Random Sampling

In this paper, alternative hybrid exponential regression-cum-ratio type estimators of finite population mean in stratified random sampling utilizing two auxiliary variables are proposed. The proposed estimators are an extension of estimator to stratified random sampling. The expressions for the bias and Mean Square Error (MSE) of the estimators are derived and asymptotic properties of the proposed estimators investigated. A comprehensive simulation study to show the efficacy of the estimators as compared to conventional estimators was carried out using Coefficient of Variation as a performance measure. The results of the simulation study have shown that the proposed estimators were not only asymptotic and more efficient, but they also produced estimates that were more precise than most of the existing estimators considered in this study.