Logarithmic Type Direct and Synthetic Estimators for Domain Mean Using Simple Random Sampling

Abstract

In this article, we propose logarithmic type direct and synthetic estima tors for the estimation of domain mean under simple random sampling. The properties such as bias and mean square error of the proposed direct and synthetic estimators are obtained up to rst order approximation. The e - ciency conditions are obtained under which the proposed direct and synthetic estimators outperform their conventional counterparts. The performance of the proposed direct and synthetic estimators is examined with the help of comprehensive computational study using real and arti cially drawn popu lations. Some appropriate suggestions are also provided to the surveyors.