Minimax Linear Estimation in a White Noise Problem

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dc.contributor.authorZhao, Linda H
dc.date2023-05-17T15:18:19.000
dc.date.accessioned2023-05-23T03:35:04Z
dc.date.available2023-05-23T03:35:04Z
dc.date.issued1997
dc.date.submitted2016-08-05T13:07:48-07:00
dc.description.abstractLinear estimation of f(x) at a point in a white noise model is considered. The exact linear minimax estimator of f(0) is found for the family of f(x) in which f′(x) is Lip (M). The resulting estimator is then used to verify a conjecture of Sacks and Ylvisaker concerning the near optimality of the Epanechnikov kernel.
dc.identifier.urihttps://repository.upenn.edu/handle/20.500.14332/47638
dc.legacy.articleid1331
dc.legacy.fields10.1214/aos/1031833671
dc.legacy.fulltexturlhttps://repository.upenn.edu/cgi/viewcontent.cgi?article=1331&context=statistics_papers&unstamped=1
dc.source.beginpage745
dc.source.endpage755
dc.source.issue270
dc.source.issue2
dc.source.journalStatistics Papers
dc.source.journaltitleThe Annals of Statistics
dc.source.peerreviewedtrue
dc.source.statuspublished
dc.source.volume25
dc.subject.otherwhite noise model
dc.subject.otherEpanechnikov kernel
dc.subject.otherlinear minimax estimation
dc.subject.otherdensity estimation
dc.subject.otherStatistics and Probability
dc.titleMinimax Linear Estimation in a White Noise Problem
dc.typeArticle
digcom.identifierstatistics_papers/270
digcom.identifier.contextkey8935683
digcom.identifier.submissionpathstatistics_papers/270
digcom.typearticle
dspace.entity.typePublication
upenn.schoolDepartmentCenterStatistics Papers
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