WAVELET BLOCK THRESHOLDING FOR DENSITY ESTIMATION IN THE PRESENCE OF BIAS

Christophe Chesneau (1)

1 LMNO - Laboratoire de Mathématiques Nicolas Oresme

We consider the density estimation problem from i.i.d. biased observations. We investigate the performances of an adaptive wavelet block thresholding estimator via the minimax approach under the Lp risk with p>=1 over Besov balls. We prove that it achieves near optimal rates of convergence.

Mots clés: Block thresholding; Adaptive estimation; Biased data; Wavelets; Block thresholding.

Domaines: Statistiques [math.ST]

Christophe Chesneau. WAVELET BLOCK THRESHOLDING FOR DENSITY ESTIMATION IN THE PRESENCE OF BIAS. 2007. ⟨hal-00169874v2⟩