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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 presents a construction rule for an objective function. This objective function generalises 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 the respective root-n estimator is asymptotically efficient and normally distributed.en_US
dc.language.isoengen_US
dc.publisheren_US
dc.relation.ispartofseriesBonn econ discussion papers 2003,16en_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-
Appears in Collections:Bonn Econ Discussion Papers, Bonn Graduate School of Economics (BGSE), Universität Bonn

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