On pointwise adaptive nonparametric deconvolution
Let \(f\) be an unknown function from which only convoluted observations under white noise are available. In this paper kernel smoothing is applied to obtain nonparametric estimators of \(f(t_0)\) that can adapt to the unknown smoothness of \(f\) and achieve the minimax rate of convergence.
scientific article; zbMATH DE number 1396209