Uniform k-Tuple Partially Rank-Ordered Set Sampling

Marvin Javier and Kaushik Ghosh

Communications in Statistics - Theory and Methods, 2023, vol. 52, issue 7, 2338-2355

Abstract: Ranked Set Sampling (RSS), introduced by McIntyre, and other related methods, such as Partially Rank-Ordered Set Sampling (PROSS), have shown that inclusion of a ranking mechanism produces estimators with lower variance than their simple random sample (SRS)-based counterparts. Like RSS, PROSS takes only one measurement from each partially ranked-ordered set. We propose a sampling plan called Uniform k-Tuple Partially Rank-Ordered (UKPRSS) where a measurement is collected from each group of a partially rank-ordered set. This article demonstrates estimators from UKPRSS have lower variance than their SRS counterparts. In addition, there is a reduction in the number units needing to be screened when compared to PROSS. Estimation of the mean and distribution function are investigated theoretically.

Date: 2023
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DOI: 10.1080/03610926.2021.1952266

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