Universal Adaptive Estimations and Confidence Intervals in the Nonparametric Statistics

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dc.creatorOstrovsky, Eugene
dc.creatorSirota, Leonid
dc.date2004-06-25
dc.date.accessioned2026-07-07T05:09:42Z
dc.date.available2026-07-07T05:09:42Z
dc.descriptionThe paper considers so-called adaptive estimations of regression, distribution density and spectral density of a Gaussian stationary sequence, asymptotically optimal in order at a growing number of observation on any regular subspace compactly embedded in space $L_2$, and confidence intervals, also adaptive, are constructed on their basis for the estimated functions in an integral norm.
dc.identifierhttps://arxiv.org/abs/math/0406535
dc.identifierhttp://arxiv.org/abs/math/0406535
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/71681
dc.subjectProbability
dc.subjectFunctional Analysis
dc.subject14J32
dc.titleUniversal Adaptive Estimations and Confidence Intervals in the Nonparametric Statistics
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