On multistage ranked set sampling for distribution and median estimation

Abstract

A variation of ranked set sampling (RSS), multistage RSS (MSRSS), is investigated for the estimation of the distribution function and some of its quantiles, in particular the median. It is shown that this method is significantly more efficient than simple random sampling (SRS). The method becomes more and more effective as the number of stages r increases. Two estimators of the median based on MSRSS are proposed and compared to the sample median obtained by SRS.