A new variable bandwidth selector for kernel estimation is proposed. The application of this bandwidth selector leads to kernel estimates that achieve optimal rates of convergence over Besov classes. This implies that the
procedure adapts to spatially inhomogeneous smoothness. In particular, the estimates share optimality properties with wavelet estimates based on thresholding of empirical wavelet coefficients.
Publié le : 1997-06-14
Classification:
Kernel estimate,
bandwidth choice,
Besov spaces,
spatial adaptation,
minimax rate of convergence,
62G07
@article{1069362731,
author = {Lepski, O. V. and Mammen, E. and Spokoiny, V. G.},
title = {Optimal spatial adaptation to inhomogeneous smoothness: an approach based on kernel estimates with variable bandwidth selectors},
journal = {Ann. Statist.},
volume = {25},
number = {6},
year = {1997},
pages = { 929-947},
language = {en},
url = {http://dml.mathdoc.fr/item/1069362731}
}
Lepski, O. V.; Mammen, E.; Spokoiny, V. G. Optimal spatial adaptation to inhomogeneous smoothness: an approach based on kernel estimates with variable bandwidth selectors. Ann. Statist., Tome 25 (1997) no. 6, pp. 929-947. http://gdmltest.u-ga.fr/item/1069362731/