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@inproceedings{578521,
author = {Koláček, Jan},
address = {Německá republika},
booktitle = {Proceedings in Computational Statistics COMPSTAT'04},
edition = {1},
keywords = {Bandwidth selection; nonparametric regression;Fourier transform; kernel estimation},
howpublished = {paměťový nosič},
language = {eng},
location = {Německá republika},
isbn = {3-7908-1554-3},
pages = {1329 - 1336},
publisher = {Springer},
title = {Use of Fourier transformation for kernel smoothing},
year = {2004}
}
TY - JOUR
ID - 578521
AU - Koláček, Jan
PY - 2004
TI - Use of Fourier transformation for kernel smoothing
PB - Springer
CY - Německá republika
SN - 3790815543
KW - Bandwidth selection
KW - nonparametric regression;Fourier transform
KW - kernel estimation
N2 - The problem of bandwidth selection for non-parametric kernel regression is considered. We will follow the Nadaraya - Watson and local linear estimators especially. The circular design is assumed in this work to avoid the difficulties caused by boundary effects. Most of bandwidth selectors are based on the residual sum of squares (RSS). It is often observed in simulation studies that these selectors are biased toward undersmoothing. This leads to consideration of a procedure which stabilizes the RSS by modifying the periodogram of the observations. Simulation studies suggest that the proposed selector is much more consistent than the classical one.
ER -
KOLÁČEK, Jan. Use of Fourier transformation for kernel smoothing. In \textit{Proceedings in Computational Statistics COMPSTAT'04}. 1. vyd. Německá republika: Springer, 2004, s.~1329 - 1336. ISBN~3-7908-1554-3.
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