Estimation of the population mean by successive use of an auxiliary variable in median ranked set sampling

Abstract

Median ranked set sampling is a sampling procedure used to estimate the population mean when the variable of interest is difficult or costly to measure. Two estimators for the population mean based on the minimum and maximum values of the auxiliary variable are built upon a successive use of ranks, second raw moments, and the linearly transformed auxiliary variable. The biases and the mean square errors of the estimators are derived. The proposed estimators under median ranked set sampling have higher efficiencies than the ratio, regression, difference-cum-ratio, and exponential estimators.