A note on wavelet estimation of the derivatives of a regression function in a random design setting

Christophe Chesneau (1)

1 LMNO - Laboratoire de Mathématiques Nicolas Oresme

We investigate the estimation of the derivatives of a regression function in the nonparametric regression model with random design. New wavelet estimators are developed. Their performances are evaluated via the mean integrated squared error. Fast rates of convergence are obtained for a wide class of unknown functions.

Mots clés: Nonparametric regression; Derivatives function estimation; Wavelets; Besov balls; Hard thresholding

Domaines: Statistiques [math.ST]; Théorie [stat.TH]

Christophe Chesneau. A note on wavelet estimation of the derivatives of a regression function in a random design setting. 2014. ⟨hal-00925546⟩