A new efficient class of estimators of finite population mean in simple random sampling

Abstract

The crux of the paper is to develop a very general class of estimators for population mean $$ \bar{Y} $$ of the study variable $$ y $$ using information on auxiliary variable $$ x $$ in simple random sampling. It has been shown that a large number of known and unknown estimators are members of the suggested class of estimators. Expressions of bias and mean squared errors of the proposed class of estimators have been obtained under large sample approximation. Asymptotic optimum estimator (AOE) in the proposed class of estimators has been obtained with its mean squared error formula. An empirical study is carried out to demonstrate the superiority of the members of the proposed class of estimators over existing estimators.