Confidence Intervals for Adaptive Regression Estimation
Résumé
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.