Please use this identifier to cite or link to this item: https://research.matf.bg.ac.rs/handle/123456789/156
DC FieldValueLanguage
dc.contributor.authorJovanović, Milanen_US
dc.contributor.authorMilošević, Bojanaen_US
dc.contributor.authorObradović, Markoen_US
dc.contributor.authorVidović, Zoranen_US
dc.date.accessioned2022-08-06T16:46:15Z-
dc.date.available2022-08-06T16:46:15Z-
dc.date.issued2021-01-01-
dc.identifier.issn03545180en
dc.identifier.urihttps://research.matf.bg.ac.rs/handle/123456789/156-
dc.description.abstractIn this paper we estimate R = P{X < Y} when X and Y are independent random variables following the Peng-Yan extended Weibull distribution. We find maximum likelihood estimator of R and its asymptotic distribution. This asymptotic distribution is used to construct asymptotic confidence intervals. In the case of equal shape parameters, we derive the exact confidence intervals, too. A procedure for deriving bootstrap-p confidence intervals is presented. The UMVUE of R and the UMVUE of its variance are derived and also the Bayes point and interval estimator of R for conjugate priors are obtained. Finally, we perform a simulation study in order to compare these estimators and provide a real data example.en_US
dc.language.isoenen_US
dc.publisherNiš : Prirodno-matematički fakulteten_US
dc.relation.ispartofFilomaten_US
dc.subjectBayes estimatoren_US
dc.subjectBootstrap confidence intervalsen_US
dc.subjectExtended Weibull distributionen_US
dc.subjectMaximum likelihood estimatoren_US
dc.subjectstress-strengthen_US
dc.subjectUMVUEen_US
dc.titleInference on reliability of stress-strength model with Peng-Yan extended Weibull distributionsen_US
dc.typeArticleen_US
dc.identifier.doi10.2298/FIL2106927J-
dc.identifier.scopus2-s2.0-85120831550-
dc.identifier.isi000720746600011-
dc.identifier.urlhttps://api.elsevier.com/content/abstract/scopus_id/85120831550-
dc.contributor.affiliationProbability and Mathematical Statisticsen_US
dc.contributor.affiliationProbability and Mathematical Statisticsen_US
dc.contributor.affiliationProbability and Mathematical Statisticsen_US
dc.relation.issn2406-0933en_US
dc.description.rankM22en_US
dc.relation.firstpage1927en_US
dc.relation.lastpage1948en_US
dc.relation.volume35en_US
dc.relation.issue6en_US
item.openairetypeArticle-
item.languageiso639-1en-
item.grantfulltextnone-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.fulltextNo Fulltext-
item.cerifentitytypePublications-
crisitem.author.deptProbability and Statistics-
crisitem.author.deptProbability and Statistics-
crisitem.author.deptProbability and Statistics-
crisitem.author.orcid0000-0001-5512-0956-
crisitem.author.orcid0000-0001-8243-9794-
crisitem.author.orcid0000-0002-6826-3232-
Appears in Collections:Research outputs
Show simple item record

SCOPUSTM   
Citations

6
checked on Dec 10, 2025

Page view(s)

18
checked on Jan 19, 2025

Google ScholarTM

Check

Altmetric

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.