Improved Ratio-type Estimators of Population Mean In Ranked Set Sampling Using Two Concomitant Variables

Abstract

In this paper, we propose an efficient class of ratio-in-exponential-type estimators with two concomitant variables using Ranked Set Sampling (RSS) scheme which improves the available estimators. The biases and mean square errors (MSEs) of the proposed estimators are obtained up to first degree approximation. Comparisons among the proposed and competitor estimators are made both theoretically and through simulation study. It turned out that when the variable of interest and the concomitant variables jointly followed a trivariate Gamma distribution, the proposed class of estimators dominates all other competitor estimators.