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2006-06-09Buch DOI: 10.18452/3856
On adaptive estimation in partial linear models
dc.contributor.authorGolubev, Georgi
dc.contributor.authorHärdle, Wolfgang
dc.date.accessioned2017-06-15T22:21:46Z
dc.date.available2017-06-15T22:21:46Z
dc.date.created2006-06-09
dc.date.issued2006-06-09
dc.identifier.issn1436-1086
dc.identifier.urihttp://edoc.hu-berlin.de/18452/4508
dc.description.abstractThe problem of estimation of the finite dimensional parameter in a partial linear model is considered. We derive upper and lower bounds for the second minimax order risk and show that the second order minimax estimator is a penalized maximum likelihood estimator. It is well known that the performance of the estimator is depending on the choice of a smoothing parameter. We propose a practically feasible adaptive procedure for the penalization choice.eng
dc.language.isoeng
dc.publisherHumboldt-Universität zu Berlin, Wirtschaftswissenschaftliche Fakultät
dc.subjectsecond order minimax riskeng
dc.subjectAdaptive estimationeng
dc.subjectpenalized likelihoodeng
dc.subject.ddc330 Wirtschaft
dc.titleOn adaptive estimation in partial linear models
dc.typebook
dc.identifier.urnurn:nbn:de:kobv:11-10064779
dc.identifier.doihttp://dx.doi.org/10.18452/3856
dc.subject.dnb17 Wirtschaft
local.edoc.container-titleSonderforschungsbereich 373: Quantification and Simulation of Economic Processes
local.edoc.pages23
local.edoc.type-nameBuch
local.edoc.container-typeseries
local.edoc.container-type-nameSchriftenreihe
local.edoc.container-volume1997
local.edoc.container-issue100
local.edoc.container-year1997
local.edoc.container-erstkatid2135319-0

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