Rodyti trumpą aprašą

dc.contributor.authorKhamnei, Hossein Jabbari
dc.contributor.authorMeidutė-Kavaliauskienė, Ieva
dc.contributor.authorFathi, Masood
dc.contributor.authorValackienė, Asta
dc.contributor.authorGhorbani, Shahryar
dc.date.accessioned2023-09-18T16:21:00Z
dc.date.available2023-09-18T16:21:00Z
dc.date.issued2022
dc.identifier.urihttps://etalpykla.vilniustech.lt/handle/123456789/113385
dc.description.abstractIn this paper, we have considered that ranked set sampling is able to estimate the parameters of exponentiated Pareto distribution. The method with which the maximum likelihood estimators for the parameters of exponentiated Pareto distribution is studied is numerical since there is no presence or possibility of a closed-form at the hands of estimators or any other intellectual. The numerical approach is a well-suited one for this study as there has been struggles in achieving it with any other technique. In order to compare the different sampling methods, simulation studies are performed as the main technique. As for the illustrative purposes, analysis of a simulated dataset is desired for the objective of the presentation. The conclusion that we can reach based on these is that the estimators based on the ranked set sample have far better efficiency than the simple random sample at the same sample size.eng
dc.formatPDF
dc.format.extentp. 1-16
dc.format.mediumtekstas / txt
dc.language.isoeng
dc.relation.isreferencedbyScience Citation Index Expanded (Web of Science)
dc.relation.isreferencedbyScopus
dc.relation.isreferencedbyCurrent Contents
dc.source.urihttps://repository.mruni.eu/handle/007/18455
dc.titleParameter Estimation of the Exponentiated Pareto Distribution Using Ranked Set Sampling and Simple Random Sampling
dc.typeStraipsnis Web of Science DB / Article in Web of Science DB
dcterms.licenseCreative Commons – Attribution – 4.0 International
dcterms.references25
dc.type.pubtypeS1 - Straipsnis Web of Science DB / Web of Science DB article
dc.contributor.institutionUniversity of Tabriz
dc.contributor.institutionVilniaus Gedimino technikos universitetas
dc.contributor.institutionUniversity of Skövde Uppsala University
dc.contributor.institutionMykolo Romerio universitetas
dc.contributor.institutionUniversity of Sakarya
dc.contributor.facultyVerslo vadybos fakultetas / Faculty of Business Management
dc.subject.researchfieldS 003 - Vadyba / Management
dc.subject.vgtuprioritizedfieldsEV03 - Dinamiškoji vadyba / Dynamic Management
dc.subject.ltspecializationsL103 - Įtrauki ir kūrybinga visuomenė / Inclusive and creative society
dc.subject.enefficiency
dc.subject.enexponentiated Pareto distribution
dc.subject.enmaximum likelihood estimator
dc.subject.enorder statistics
dc.subject.enranked set sampling
dc.subject.ensimple random sampling
dcterms.sourcetitleAxioms
dc.description.issueiss. 3
dc.description.volumevol. 11
dc.publisher.nameMDPI
dc.publisher.cityBasel
dc.identifier.doi1
dc.identifier.doi000816488100001
dc.identifier.doi10.3390/axioms11060293
dc.identifier.elaba133920357


Šio įrašo failai

FailaiDydisFormatasPeržiūra

Su šiuo įrašu susijusių failų nėra.

Šis įrašas yra šioje (-se) kolekcijoje (-ose)

Rodyti trumpą aprašą