New double stage ranked set sampling for estimating the population mean


In environmental and many other areas, the main focus of survey is to measureelements using an efficient and cost-effective sampling technique. One way to reach that isby using Ranked set sampling (RSS). RSS is an alternative sampling technique that canimprove the efficiency of estimators when measuring the variable of interest is eithercostly or time-consuming but ranking its elements in a small set is easy. The purpose of thisarticle is to introduce a new modification of RSS to estimate the mean of the targetpopulation. This proposed technique is a double-stage approach that combines median RSS(MRSS) and MiniMax RSS (MMRSS). The performance of the empirical mean and varianceestimators based on the proposed technique are compared with their counterparts inMMRSS, RSS and simple random sampling (SRS) via Monte Carlo simulation. Simulationresults revealed that this new modification is always more efficient than their counterpartsusing MMRSS and SRS, while it is more efficient than RSS is many cases especially when thedistribution is asymmetric.

DOI Code: 10.1285/i20705948v15n2p463

Keywords: Double stage, Efficiency, Mean Estimation, Median ranked set sampling; Minimax ranked set sampling; Monte Carlo simulation.

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