Regression cum exponential quadratic product type estimator of the population mean in SRS

Abstract

Using the information of auxiliary variables the present study examines exponential estimator for population mean under the scheme of simple random sampling (SRS). The study envisaged a class of regression cum exponential quadratic ratio type estimator under SRS to estimate the mean of population. The bias and mean square error (MSE) for the optimal values of the constant implicated in the proposed estimator has been determined. We also have compared the suggested estimator’s efficiency to that of other standard estimators. The envisaged exponential estimator is revealed to be more effective as compared to the mean per unit, product-type and ratio-type exponential estimators under optimum conditions. The numerical illustration also shows that the given estimator has improved performance as compare to traditional estimators available in literature.