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Confidence Intervals for Adaptive Regression Estimation

Anatoli Juditsky 1 Oleg Lepski
1 IS2 - Statistical Inference for Industry and Health
Inria Grenoble - Rhône-Alpes, LBBE - Laboratoire de Biométrie et Biologie Evolutive - UMR 5558
Abstract : The problem of adaptive estimation of the regression function f from noisy observation is concerned. A wavelet adaptive estimator of unknown function with the confidence interval for the L_2-error are provided. We show that if f belongs to a Sobolev class, the proposed estimate and the associated confidence interval are minimax.
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https://hal.inria.fr/inria-00073101
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Submitted on : Wednesday, May 24, 2006 - 11:51:57 AM
Last modification on : Monday, February 10, 2020 - 4:36:45 PM
Long-term archiving on: : Sunday, April 4, 2010 - 11:34:08 PM

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  • HAL Id : inria-00073101, version 1

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Anatoli Juditsky, Oleg Lepski. Confidence Intervals for Adaptive Regression Estimation. RR-3580, INRIA. 1998. ⟨inria-00073101⟩

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