2004/04/01 by Yannick Baraud · 2 citations
Computer Science · Mathematics · #Gaussian Processes and Bayesian Inference #Random Matrices and Applications #Statistical Methods and Inference #math.ST #msc:62G05 #msc:62G10. #msc:62G15 #stat.TH
paper · pdf · doi:10.1214/009053604000000085
published as Annals of Statistics 2004, Vol. 32, No. 2, 528-551
openalex publication_date 2004/04/01 · arxiv created 2004/06/22 · arxiv updated 2009/12/01 · openalex created_date 2016/06/24 · openalex updated_date 2026/07/30
Starting from the observation of an ℝn-Gaussian vector of mean f and covariance matrix σ2In (In 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.