Adaptive wavelet estimator for nonparametric density deconvolution
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[The problem of estimating a density g based on a sample X1, X2,..., Xn from p = q * g is considered. Linear and nonlinear wavelet estimators based on Meyer-type wavelets are constructed. The estimators are asymptotically optimal and adaptive if g belongs to the Sobolev space H. Moreover, the estimators considered in this paper adjust automatically to the situation when g is supersmooth.]