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General EM algorithm for fitting non-monotone hazard functions from truncated and censored observations

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dc.contributor.authorSTEPHANE, BARDE-
dc.contributor.authorKo, Young Myoung-
dc.contributor.authorShin, Hayong-
dc.date.accessioned2023-07-05T05:32:29Z-
dc.date.available2023-07-05T05:32:29Z-
dc.date.issued2022-09-
dc.identifier.issn0167-6377-
dc.identifier.issn1872-7468-
dc.identifier.urihttps://scholarworks.bwise.kr/erica/handle/2021.sw.erica/112923-
dc.description.abstractRecently, many researchers focused on modeling non-monotonic hazard functions such as bath-tube and hump shapes. However, most of their estimation methods are focused on complete observations. Since reliability data are typically censored and truncated, a general EM algorithm is proposed, which can fit any of those complex hazard functions. The proposed EM algorithm is analyzed by fitting well-known 4-parameter hazard functions, where its performance is compared by their specific direct methods through extensive Monte Carlo simulations. © 2022 Elsevier B.V.-
dc.format.extent8-
dc.language영어-
dc.language.isoENG-
dc.publisherElsevier BV-
dc.titleGeneral EM algorithm for fitting non-monotone hazard functions from truncated and censored observations-
dc.typeArticle-
dc.publisher.location네델란드-
dc.identifier.doi10.1016/j.orl.2022.07.001-
dc.identifier.scopusid2-s2.0-85134263111-
dc.identifier.wosid000831092200004-
dc.identifier.bibliographicCitationOperations Research Letters, v.50, no.5, pp 476 - 483-
dc.citation.titleOperations Research Letters-
dc.citation.volume50-
dc.citation.number5-
dc.citation.startPage476-
dc.citation.endPage483-
dc.type.docType정기학술지(Article(Perspective Article포함))-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaOperations Research & Management Science-
dc.relation.journalWebOfScienceCategoryOperations Research & Management Science-
dc.subject.keywordPlusBATHTUB-SHAPED HAZARD-
dc.subject.keywordPlusWEIBULL DISTRIBUTION-
dc.subject.keywordPlusDISTRIBUTIONS-
dc.subject.keywordAuthorEM algorithm-
dc.subject.keywordAuthorHazard function-
dc.subject.keywordAuthorLeft-truncated & right-censored-
dc.subject.keywordAuthorPhase-type distribution-
dc.subject.keywordAuthorSequential quadratic programming-
dc.identifier.urlhttps://www.sciencedirect.com/science/article/pii/S0167637722000803?pes=vor-
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ERICA 공학대학 (DEPARTMENT OF INDUSTRIAL & MANAGEMENT ENGINEERING)
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