Uniform k-tuple Partially Rank-Ordered Set Sampling

Thomas M. Menino Convention & Exhibition Center 

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 produ-
ces estimators with lower variance than their simple random sample
(SRS)-based counterparts. Like RSS, PROSS takes only one measure-
ment 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 com-
pared to PROSS. Estimation of the mean and distribution function
are investigated theoretically.

Ranked Set Sampling

Partially Rank-Ordered Set Sampling

k-tuple Ranked Set Sampling

k-tuple Partially Rank-Ordered Set Sampling 

IMS