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dc.contributor.authorGürler, Ü.en_US
dc.contributor.authorYenigün, C. D.en_US
dc.date.accessioned2015-07-28T12:00:40Z
dc.date.available2015-07-28T12:00:40Z
dc.date.issued2011-04-27en_US
dc.identifier.issn0167-9473
dc.identifier.urihttp://hdl.handle.net/11693/12228
dc.description.abstractHazard function plays an important role in reliability and survival analysis. In some real life applications, abrupt changes in the hazard function may be observed and it is of interest to detect the location and the size of the change. Hazard models with a changepoint are considered when the observations are subject to random left truncation and right censoring. For a piecewise constant hazard function with a single change-point, two estimation methods based on the maximum likelihood ideas are considered. The first method assumes parametric families of distributions for the censoring and truncation variables, whereas the second one is based on conditional likelihood approaches. A simulation study is carried out to illustrate the performances of the proposed estimators. The results indicate that the fully parametric method performs better especially for estimating the size of the change, however the difference between the two methods vanish as the sample size increases. It is also observed that the full likelihood approach is not robust to model misspecification.en_US
dc.language.isoEnglishen_US
dc.source.titleComputational Statistics and Data Analysisen_US
dc.relation.isversionofhttp://dx.doi.org/10.1016/j.csda.2011.04.014en_US
dc.subjectHazard functionen_US
dc.subjectChange-pointen_US
dc.subjectConditional likelihooden_US
dc.subjectLeft truncated right censored dataen_US
dc.titleFull and conditional likelihood approaches for hazard change-point estimation with truncated and censored dataen_US
dc.typeArticleen_US
dc.departmentDepartment of Managementen_US
dc.departmentDepartment of Industrial Engineeringen_US
dc.citation.spage2856en_US
dc.citation.epage2870en_US
dc.citation.volumeNumber55en_US
dc.citation.issueNumber10en_US
dc.identifier.doi10.1016/j.csda.2011.04.014en_US
dc.publisherElsevieren_US
dc.identifier.eissn1872-7352


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