New highly efficient one and two-stage ranked set sampling variations

Abstract

In this paper, we proposed highly efficient ranked set sampling schemes to estimate the population mean. First, we proposed a new single-stage sampling scheme which we called new neoteric ranked set sampling. Second, we proposed a two-stage methods based on the systematic ranked set sampling and the new neoteric ranked set sampling. The performance of the proposed methods is compared with that of competitive two-stage methods through a Monte Carlo simulation study using various popular symmetric and asymmetric statistical distributions. The results show that the newly proposed methods are more efficient in estimating the population mean than the existing methods. The proposed methods are illustrated on data of the diameter and height of pine trees.