Uniform k-Tuple Partially Rank-Ordered Set Sampling
Document Type
Article
Publication Date
7-19-2021
Publication Title
Communications in Statistics: Theory and Methods
First page number:
1
Last page number:
18
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.
Keywords
Ranked set sampling; Partially rank-ordered set sampling; k-Tuple Ranked set sampling; k-Tuple partially rank-ordered set sampling
Disciplines
Mathematics
Language
English
Repository Citation
Javier, M.,
Ghosh, K.
(2021).
Uniform k-Tuple Partially Rank-Ordered Set Sampling.
Communications in Statistics: Theory and Methods
1-18.
http://dx.doi.org/10.1080/03610926.2021.1952266