Hartly Ross Type Unbiased Estimator in Stratified Ranked Set Sampling Using Two Auxiliary Variables

Abstract

Ranked set sampling has gained much attention of the research in the
recent past due to its enhanced efficiency. In this article, we proposed
Hartly-Ross type unbiased estimator of the finite population mean using
two auxiliary variables in stratified ranked set sampling (SRSS). The
variance of the proposed unbiased estimator is derived up to first order of
approximation. Comparison among the proposed and competitor
estimators are made both theoretically and through rigorous simulation
study. It is observed that the newly suggested Hartly-Ross type estimator
is more efficient as compared to all the considered competitor estimators
under SRSS design.