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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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