Estimation of the common mean of two normal distributions using ranked set sampling and some of its variations

Abstract

The estimation of the common mean of two normal distributions based on ranked set sampling (RSS) techniques is considered. In particular, RSS, moving extreme ranked set sampling, median ranked set sampling, and steady-state ranked set sampling are used. The estimators obtained are compared with each other and with their counterparts using simple random sampling (SRS). Allocation of sample size between the two distributions is considered using Neyman allocation. It turned out that the suggested estimators are more efficient than their counterparts using SRS.