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dc.contributor.authorLepski, Oleg V.en_US
dc.date.accessioned2012-10-25en_US
dc.date.accessioned2012-11-19T15:22:04Z-
dc.date.available2012-11-19T15:22:04Z-
dc.date.issued1997en_US
dc.identifier.piurn:nbn:de:kobv:11-10064073en_US
dc.identifier.urihttp://hdl.handle.net/10419/66236-
dc.description.abstractThe new approach, allowed to take into account some additional information, coming from datas, is proposed. The main idea is to obtain from datas some information about structure of the model in order to improve accuracy of estimation. It seems to be important, since standard nonparametric accuracy of estimation is usually very low. To improve one statisticians often impose some additional structure on considerable model, that can lead to inadequate model. To avoid both these disadvantages special form of estimation procedure, based on some combination of adaptive technique and hypothesis testing, is applied. From mathematical point of view it leads to the consideration of new kind of minimax risks. From practical point of view it allows to improve accuracy of estimation procedures even for the cases when guess on special structure of a model turns out to be wrong.en_US
dc.language.isoengen_US
dc.publisherHumboldt-Universität Berlinen_US
dc.relation.ispartofseriesDiscussion Papers, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes 1997,21en_US
dc.subject.ddc330en_US
dc.titleHow to improve accuracy of estimationen_US
dc.typeWorking Paperen_US
dc.identifier.ppn728569523en_US
dc.rightshttp://www.econstor.eu/dspace/Nutzungsbedingungenen_US
dc.identifier.repecRePEc:zbw:sfb373:199721-
Appears in Collections:Discussion Papers, SFB 373, HU Berlin

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