Quartile Pair Ranked Set Sampling: Development and Estimation

Abstract

A cost-effective, efficient and anti-wasting sampling units scheme named quartile pair ranked set sampling (QPRSS) for estimating the population mean is presented in this study. This scheme offers an unbiased estimator for the population mean when the distribution is symmetric and variance of mean per unit estimator under QPRSS is always smaller than the variance of mean per unit estimator under simple random sampling (SRS). On the basis of exact ranking, Monte Carlo simulations from several symmetric and nonsymmetric distributions are utilized to assess the performance of the suggested QPRSS mean estimator. Simulation findings demonstrated that the QPRSS estimator is more efficient than their competitors using SRS, pair ranked set sampling and extreme pair ranked set sampling for all distributions considered in this study.