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dc.contributor.authorUzunoğulları, Ü.en_US
dc.contributor.authorWang, J.-L.en_US
dc.date.accessioned2016-02-08T10:55:07Z
dc.date.available2016-02-08T10:55:07Z
dc.date.issued1992en_US
dc.identifier.issn0006-3444
dc.identifier.urihttp://hdl.handle.net/11693/26109
dc.description.abstractSUMMARY: Left truncation and right censoring arise frequently in practice for life data. This paper is concerned with the estimation of the hazard rate function for such data. Two types of nonparametric estimators based on kernel smoothing methods are considered. The first one is obtained by convolving a kernel with a cumulative hazard estimator. The second one is in the form of a ratio of two statistics. Local properties including consistency, asymptotic normality and mean squared error expressions are presented for both estimators. These properties facilitate locally adaptive bandwidth choice. The two types of estimators are then compared based on their theoretical and empirical performances. The effect of overlooking the truncation factor is demonstrated through the Channing House data.en_US
dc.language.isoEnglishen_US
dc.source.titleBiometrikaen_US
dc.relation.isversionofhttps://doi.org/10.1093/biomet/79.2.297en_US
dc.subjectConsistencyen_US
dc.subjectKernel estimatoren_US
dc.subjectMean squared erroren_US
dc.subjectOptimal bandwidthen_US
dc.subjectWeak convergenceen_US
dc.titleA comparison of hazard rate estimators for left truncated and right censored dataen_US
dc.typeArticleen_US
dc.departmentDepartment of Industrial Engineeringen_US
dc.citation.spage297en_US
dc.citation.epage310en_US
dc.citation.volumeNumber79en_US
dc.citation.issueNumber2en_US
dc.identifier.doi10.1093/biomet/79.2.297en_US


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