Alternative Ratio-Product Type Estimator in Simple Random Sampling

Abstract

In this paper, we proposed a new alternative ratio-product estimator in simple random sampling without replacement by using information on an auxiliary variable. The proposed estimator is a mixture of some of the commonly known estimators. We have derived the minimum mean square errors up to the first order of approximation. Theoretically, we compare the mean square error (MSE) equation of the proposed estimator with the mean square error (MSE) equations of the existing estimators in literature. Numerical examples with four real data sets shows that the proposed estimator is more efficient than the existing other estimators considered. Therefore, the findings of this research are important in identifying alternative ratio-product exponential estimator, its properties, as well as relevant empirical applications.