Optimal rates of convergence for nonparametric regression estimation under anisotropic Hölder condition

Huijun Guo and Junke Kou

Communications in Statistics - Theory and Methods, 2024, vol. 53, issue 2, 687-699

Abstract: In the multidimensional setting, we consider the nonparametric regression estimation with errors-in-variables. Both ordinary smooth noise and super smooth one are assumed for errors in the covariates. An anisotropic kernel estimator is provided based on a deconvolution technique. We study the pointwise estimation and obtain the optimal rates of convergence under the anisotropic Hölder condition.

Date: 2024
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DOI: 10.1080/03610926.2022.2091781

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