Ratio Cum Exponential In Regression-Type Mean Estimator Incorporating Empirical Distribution Function as Dual Application of Supplementary Variable Under Stratified Random Sampling Design

Abstract

In survey sampling for valid inferences, it depends on precise estimation of finite population parameters, such as the population mean. In this study, we present Ratio Cum Exponential In Regression-Type estimator under stratified random sampling design using empirical distribution function (EDF) as a dual of auxiliary variable. The bias and Mean Square Error (MSE) of the proposed estimators are derived up to first-order approximation. The proposed estimator has the minimum MSE and higher Percentage Relative Efficiency (PRE) from all the estimators which are considered as counterpart. In stratified random sampling, the dual use of auxiliary variable ismore important when limited auxiliary information is available.