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dc.contributor.authorShahzad, Usman
dc.contributor.authorHanif, Muhammad
dc.contributor.authorKoyuncu, Nursel
dc.contributor.authorGarcia Luengo, Amelia Victoria
dc.date.accessioned2021-06-09T06:05:41Z
dc.date.available2021-06-09T06:05:41Z
dc.date.issued2019
dc.identifier.issn1303-5991
dc.identifier.urihttp://dx.doi.org/10.31801/cfsuasmas.586057
dc.identifier.urihttp://hdl.handle.net/11655/24836
dc.description.abstractKoyuncu and Kadilar [7] introduced a family of estimators under simple random sampling. In this article; we adapt these estimators for ranked set sampling. Further, we suggest a regression-type estimator of population mean utilizing available supplementary information under ranked set sampling scheme alongside the sensitivity issue when the variate of interest is sensitive. The bias and mean square error of the suggested estimator is determined theoretically for both situations. A simulation study has been done to demonstrate the percentage relative efficiency of proposed estimators over the adapted and reviewed estimators.
dc.language.isoen
dc.relation.isversionof10.31801/cfsuasmas.586057
dc.rightsAttribution 4.0 United States
dc.rightsinfo:eu-repo/semantics/openAccess
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectMean squared error
dc.subjectpercentage relative efficiency
dc.subjectranked set sampling
dc.subjectsensitivity
dc.titleA Regression Type Estimator For Mean Estimation Under Ranked Set Sampling Alongside The Sensitivity Issue
dc.typeinfo:eu-repo/semantics/article
dc.typeinfo:eu-repo/semantics/publishedVersion
dc.relation.journalCommunications Faculty Of Sciences University Of Ankara-Series A1 Mathematics And Statistics
dc.contributor.departmentİstatistik
dc.identifier.volume68
dc.identifier.issue2
dc.description.indexWoS


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