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dc.contributor.authorBarbu, Vlad Stefanen
dc.contributor.authorKaragrigoriou, Alexen
dc.contributor.authorMakrides, Andreasen
dc.creatorBarbu, Vlad Stefanen
dc.creatorKaragrigoriou, Alexen
dc.creatorMakrides, Andreasen
dc.date.accessioned2019-12-02T10:33:45Z
dc.date.available2019-12-02T10:33:45Z
dc.date.issued2016
dc.identifier.issn1387-5841
dc.identifier.urihttp://gnosis.library.ucy.ac.cy/handle/7/56460
dc.description.abstractIn this work we focus on multi state systems that we model by means of semi-Markov processes. The sojourn times are seen to be independent not identically distributed random variables and assumed to belong to a general class of distributions that includes several popular reliability distributions like the exponential, Weibull, and Pareto. We obtain maximum likelihood estimators of the parameters of interest and investigate their asymptotic properties. Plug-in type estimators are furnished for various quantities related to the system under study. © 2016 Springer Science+Business Media New Yorken
dc.sourceMethodology and Computing in Applied Probabilityen
dc.source.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-84979281172&doi=10.1007%2fs11009-016-9510-y&partnerID=40&md5=a48002052431a5cf1c014eb5e60662c9
dc.subjectParameter estimationen
dc.subjectSurvival analysisen
dc.subjectMulti-state systemen
dc.subjectReliability theoryen
dc.subjectSemi-Markov processesen
dc.subjectReliability indicatorsen
dc.titleSemi-Markov Modelling for Multi-State Systemsen
dc.typeinfo:eu-repo/semantics/article
dc.identifier.doi10.1007/s11009-016-9510-y
dc.description.startingpage1
dc.description.endingpage18
dc.author.facultyΣχολή Θετικών και Εφαρμοσμένων Επιστημών / Faculty of Pure and Applied Sciences
dc.author.departmentΤμήμα Μαθηματικών και Στατιστικής / Department of Mathematics and Statistics
dc.type.uhtypeArticleen
dc.description.notes<p>Cited By :1en
dc.description.notesArticle in Press</p>en
dc.source.abbreviationMethodol.Comput.Appl.Probab.en
dc.contributor.orcidKaragrigoriou, Alex [0000-0002-4919-2133]


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