Article Dans Une Revue Advances in Statistical Analysis Année : 2012

Adaptive wavelet estimation of a function in an indirect regression model

Résumé

We consider a nonparametric regression model where m noiseperturbed functions f1, . . . , fm are randomly observed. For a fixed ν ∈ {1, . . . ,m}, we want to estimate fν from the observations. To reach this goal, we develop an adaptive wavelet estimator based on a hard thresholding rule. Adopting the mean integrated squared error over Besov balls, we prove that it attains a sharp rate of convergence. Simulation results are reported to support our theoretical findings.

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hal-00809249 , version 1 (08-04-2013)

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Christophe Chesneau, Jalal M. Fadili. Adaptive wavelet estimation of a function in an indirect regression model. Advances in Statistical Analysis, 2012, 96 (1), pp.25-46. ⟨10.1007/s10182-011-0157-2⟩. ⟨hal-00809249⟩
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