CLASS OF REGRESSION CUM-DUAL ESTIMATOR IN SIMPLE RANDOM SAMPLING

Abstract

This research work propose a class of regression estimator with cum-dual ratio estimator as intercept for estimating the mean of the study variable y using auxiliary variable x. It also propose a class of regression estimator with cum-dual product estimator as intercept for estimating the mean of the study variable y using auxiliary variable x. The bias and the mean square error of the proposed estimators were obtained, also, the asymptotically optimum estimator (AOE) was obtained along with its mean square error. Both analytical and numerical comparisons have shown the proposed estimators to be more efficient than the usual simple random sampling estimator and ratio estimator, product estimator, cum-dual ratio and product estimator, and ratio-cum-dual to ratio and product-cum-dual to product estimator proposed. Numerical validation of the proposed estimator was done to show the superiority of the proposed estimators over the usual simple random sampling estimator and ratio estimator, product estimator, dual to ratio and dual to product estimator. Also, the proposed estimators agree with cum-dual ratio estimator and cum-dual product estimators.