Nonparametric estimation of hazard functions and their derivatives under truncation model

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dc.citation.epage264en_US
dc.citation.issueNumber2en_US
dc.citation.spage249en_US
dc.citation.volumeNumber45en_US
dc.contributor.authorGürler, Ü.en_US
dc.contributor.authorWang, J. -L.en_US
dc.date.accessioned2016-02-08T10:54:11Z
dc.date.available2016-02-08T10:54:11Z
dc.date.issued1993en_US
dc.departmentDepartment of Industrial Engineeringen_US
dc.description.abstractNonparametric kernel estimators for hazard functions and their derivatives are considered under the random left truncation model. The estimator is of the form of sum of identically distributed but dependent random variables. Exact and asymptotic expressions for the biases and variances of the estimators are derived. Mean square consistency and local asymptotic normality of the estimators are established. Adaptive local bandwidths are obtained by estimating the optimal bandwidths consistently. © 1993 The Institute of Statistical Mathematics.en_US
dc.identifier.doi10.1007/BF00775812en_US
dc.identifier.issn0020-3157
dc.identifier.urihttp://hdl.handle.net/11693/26044
dc.language.isoEnglishen_US
dc.publisherKluwer Academic Publishersen_US
dc.relation.isversionofhttp://dx.doi.org/10.1007/BF00775812en_US
dc.source.titleAnnals of the Institute of Statistical Mathematicsen_US
dc.subjectAdaptive bandwidth choiceen_US
dc.subjectConsistencyen_US
dc.subjectHájek projectionen_US
dc.subjectKernel estimateen_US
dc.subjectMean square erroren_US
dc.subjectTightnessen_US
dc.titleNonparametric estimation of hazard functions and their derivatives under truncation modelen_US
dc.typeArticleen_US

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