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dc.creatorMinić, Marija
dc.date.accessioned2020-09-22T13:58:04Z
dc.date.available2020-09-22T13:58:04Z
dc.date.issued2020
dc.identifier.issn0354-0243
dc.identifier.urihttps://farfar.pharmacy.bg.ac.rs/handle/123456789/3660
dc.description.abstractThe ranked set sampling (RSS) is a cost-effective method of sampling thatcan be used in a wide range of statistical problems. In this paper, the shape and thescale parameters of Nadarajah-Haghighi extension of the exponential distribution areestimated based on a simple random sample (SRS) and RSS. Three cases are considered:1) the scale parameter is known; 2) the shape parameter is known; 3) both shape andscale parameters are unknown. Observations are done when the ranking mechanism inthe ranked set sample is perfect and when it is not. Method of moments, the maximumlikelihood method, and a modification of the maximum likelihood method are used. Theobtained estimators are compared in terms of their biases and mean square errors (MSE).The results revealed that estimators based on RSS tend to show better properties (smallerbias and MSE) relative to their SRS counterparts, regardless of the quality of the ranking.en
dc.publisherBelgrade : Faculty of Organizational Sciences
dc.rightsopenAccess
dc.rights.urihttps://creativecommons.org/licenses/by-nc-sa/4.0/
dc.sourceYugoslav Journal of Operations Research
dc.subjectImperfect Ranking
dc.subjectNadarajah-Haghighi Extension of the Exponential Eistribution
dc.subjectRanked set Sampling
dc.subjectSimple Random Sampling
dc.titleESTIMATION OF PARAMETERS OF NADARAJAH-HAGHIGHI EXTENSION OF THE EXPONENTIAL DISTRIBUTION USING PERFECT AND IMPERFECT RANKED SET SAMPLEen
dc.typearticle
dc.rights.licenseBY-NC-SA
dcterms.abstractМинић, Марија;
dc.citation.volume30
dc.citation.issue2
dc.citation.spage177
dc.citation.epage198
dc.citation.rankM24
dc.identifier.doi10.2298/YJOR190415027M
dc.identifier.scopus2-s2.0-85090530229
dc.identifier.fulltexthttps://farfar.pharmacy.bg.ac.rs/bitstream/id/8070/ESTIMATION_OF_PARAMETERS_PUB_2020.pdf
dc.type.versionpublishedVersion


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