Distribution function estimation using concomitant-based ranked set sampling
Abstract
Ranked set sampling (RSS) is a data collection method designed to exploit auxiliary ranking information. In this paper, a new estimator of distribution function is proposed when RSS is done by using a concomitant variable. It is shown by simulation study that the alternative estimator can be considerably more efficient than the standard one, especially when the rankings are perfect.
Keywords
References
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Details
Primary Language
English
Subjects
Mathematical Sciences
Journal Section
Research Article
Publication Date
June 1, 2018
Submission Date
February 10, 2016
Acceptance Date
August 28, 2016
Published in Issue
Year 2018 Volume: 47 Number: 3