Alternative Ratio - Regression Type Estimator in Simple Random Sampling

Abstract

In this study, an alternative ratio-regression type estimator was proposed which was compared with Kadilar and Cingi (2004), and Ekaete et al. (2014) estimators. This proposed estimator combined classical ratio estimator with our usual regression estimator. The same data set used by Kadilar and Cingi (2004) and Ekaete et al. (2014) were also used to determine the efficiency of this alternative ratio-regression type estimator. The finding was that, when α=1, Ekaete et al. (2014) was found to be better but  at , this alternative ratio-regression type estimator was said to be more efficient than both Kadilar and Cingi (2004), and Ekaete et al. (2014) estimators based on their estimated mean square error (mse).