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Article Dans Une Revue Annals of Statistics Année : 2004

Confidence balls in Gaussian regression

Résumé

Starting from the observation of an R^n-Gaussian vector of mean f and covariance matrix \\sigma^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.

Dates et versions

hal-00012909 , version 1 (29-10-2005)

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Citer

Yannick Baraud. Confidence balls in Gaussian regression. Annals of Statistics, 2004, 32,No.2, pp.528-551. ⟨hal-00012909⟩
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