Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/22865
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dc.contributor.authorSchnedler, Wendelinen_US
dc.date.accessioned2009-01-29T15:10:30Z-
dc.date.available2009-01-29T15:10:30Z-
dc.date.issued2003en_US
dc.identifier.urihttp://hdl.handle.net/10419/22865-
dc.description.abstractThis article considers a wide class of censoring problems and presentsa construction rule for an objective function. This objective functiongeneralises the ordinary likelihood as well as particular "likelihoods"used for estimation in several censoring models. Under regularity con-ditions the maximiser of this generalised likelihood has all the prop-erties of a maximum likelihood estimator: it is consistent and therespective root-n estimator is asymptotically efficient and normallydistributed.en_US
dc.language.isoengen_US
dc.publisheren_US
dc.relation.ispartofseries|aBonn econ discussion papers |x2003,16en_US
dc.subject.jelC13en_US
dc.subject.jelC24en_US
dc.subject.ddc330en_US
dc.subject.keywordCensored variablesen_US
dc.subject.keywordM-estimationen_US
dc.subject.keywordMultivariate methodsen_US
dc.subject.keywordRandom censoringen_US
dc.subject.keywordgeneralised likelihooden_US
dc.subject.stwTobit-Modellen_US
dc.subject.stwSchätztheorieen_US
dc.subject.stwTheorieen_US
dc.titleWhat you always wanted to know about censoring but never dared to asken_US
dc.typeWorking Paperen_US
dc.identifier.ppn38289118Xen_US
dc.rightshttp://www.econstor.eu/dspace/Nutzungsbedingungen-

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