On the accuracy of the uniform approximation of universal local constant kernel estimators to smooth regression functions

On the accuracy of the uniform approximation of universal local constant kernel estimators to smooth regression functions

(Russian, English abstract)

Linke Yu. Yu.
Siberian Electronic Mathematical Reports, 21, 2, pp. 1450-1459 (2024)

УДК 519.234 
DOI: 10.33048/semi.2024.21.092  
MSC 62G08


Abstract:

The paper considers universal locally constant kernel estimators in nonparametric regression. Previously, these estimators were studied only in the case of a continuous regression function. It is shown that with the additional condition of smoothness of the regression function, the accuracy of the uniform approximation can be improved.

Keywords: nonparametric regression, universal local constant kernel estimator, uniform consistency, fixed design, random design