Modified Class of Estimator for Finite Population Mean Under Two-Phase Sampling Using Regression Estimation Approach
A. Y. Erinola *
Department of Mathematics, Kebbi State University of Science and Technology, Aliero, Nigeria.
R. V. K. Singh
Department of Mathematics, Kebbi State University of Science and Technology, Aliero, Nigeria.
A. Audu
Department of Mathematics, Usmanu Danfodiyo University, Sokoto, Nigeria.
T. James
Department of Mathematics, Kebbi State University of Science and Technology, Aliero, Nigeria.
*Author to whom correspondence should be addressed.
Abstract
This study proposed modified a class of estimator in simple random sampling for the estimation of population mean of the study variable using as axillary information. The biases and MSE of suggested estimators were derived up to the first order approximation using Taylor’s series expansion approach. Theoretically, the suggested estimators were compared with the existing estimators in the literature. The mean square errors (MSE) and percentage relative efficiency (PRE) of proposed estimators and that of some existing estimators were computed numerically and the results revealed that the members of the proposed class of estimator were more efficient compared to their counterparts and can produce better estimates than other estimators considered in the study.
Keywords: Auxiliary attribute, ratio-exponential estimators, mean square error, efficiency, two-phase sampling