Efficiency bounds for a generalization of ranked-set sampling

Timothy G. Feeman and Jesse Frey

Communications in Statistics - Theory and Methods, 2016, vol. 45, issue 3, 739-756

Abstract: Partially rank-ordered set sampling (PROSS) is a generalization of ranked-set sampling (RSS) in which the ranker is not required to give a full ranking in each set. In this paper, we compare the efficiency of the sample mean as an estimator of the population mean under PROSS, RSS, and simple random sampling (SRS). We find that for fixed set size and total sample size, the efficiency of PROSS falls between that of SRS and that of RSS. We also develop a method for finding a sharp upper bound on the efficiency of PROSS relative to SRS for a particular design.

Date: 2016
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DOI: 10.1080/03610926.2013.835418

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