Increasing the efficiency of ranked set sampling via visual grouping with respect to a threshold - Mohd T. Alodat, Mohammed K. Shakhatreh, Sameer A. Al-Subh - Vita e Pensiero - Articolo Statistica & Applicazioni

Increasing the efficiency of ranked set sampling via visual grouping with respect to a threshold

digital Increasing the efficiency of ranked set sampling
via visual grouping with respect to a threshold
Article
journal STATISTICA & APPLICAZIONI
issue STATISTICA & APPLICAZIONI - 2019 - 1
title Increasing the efficiency of ranked set sampling via visual grouping with respect to a threshold
Authors , , ,
Publisher Vita e Pensiero
format Article | Pdf
online since 08-2020
doi 10.26350/999999_000021
issn 1824-6672 (print) | 2283-6659 (digital)
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In this paper, a new sampling technique is proposed that carries more information than contained in ranked set sample (RSS). The proposed sampling technique is defined by making the use for the idea of visual grouping of population units with respect to a fixed threshold and RSS. We refer to it as RSS-Grouping technique. Under the best informative RSS-Grouping technique, the maximum likelihood estimator (MLE) of the mean of an exponential distribution is derived. This MLE is then compared to various candidate estimators through extensive simulation experiments. Numerical results show that the MLE under the best informative RSS-Grouping scheme is preformed better thanthese estimators. The effects of imperfect sampling on the behavior of the MLE under the proposed scheme is also studied. We conduct a simulation study to assess the finite sample behavior of the MLE under imperfect sampling and imperfect classification of visual grouping. Similarly, the simulation study shows that the MLE is behaved asymptotically unbiased. Additionally, the MLE tends to be at least as efficient as the MLE under RSS regardless of raking errors and the estimation of the threshold has slightly effects on the sampling distribution of the MLE.

keywords

Exponential Distribution, Maximum Likelihood, Ranked Set Sampling, Simple Random Sample, Threshold

Authors biography

Department of Statistics -Yarmouk University - IRBID, Jordan (e-mail:malodat @yu.edu.jo); Department of Mathematics and Statistics - Jordan University of Science and Technology - IRBID, Jordan (e-mail: mkshakhatreh6@just.edu.jo); Department of Mathematics - Jordan University of Science and Technology - IRBID, Jordan (Email: salsubh@mutah.edu.jo ); Department of Mathematics and Statistics - La Trope University - Australia (e-mail:omaridt84@yahoo.com).

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