Confidence balls in Gaussian regression

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dc.creatorBaraud, Yannick
dc.date2004-06-22
dc.date.accessioned2026-07-07T08:06:18Z
dc.date.available2026-07-07T08:06:18Z
dc.descriptionStarting from the observation of an R^n-Gaussian vector of mean f and covariance matrix σ^2 I_n (I_n is the identity matrix), we propose a method for building a Euclidean confidence ball around f, with prescribed probability of coverage. For each n, we describe its nonasymptotic property and show its optimality with respect to some criteria.
dc.identifierhttps://arxiv.org/abs/math/0406425
dc.identifierhttp://arxiv.org/abs/math/0406425
dc.identifierAnnals of Statistics 2004, Vol. 32, No. 2, 528-551
dc.identifierdoi:10.1214/009053604000000085
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/130559
dc.subjectStatistics Theory
dc.subject62G15 (Primary) 62G05, 62G10. (Secondary)
dc.titleConfidence balls in Gaussian regression
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