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@article{634140,
author = {Koláček, Jan},
article_location = {Germany},
article_number = {1},
keywords = {bandwidth selection; Fourier transform; kernel estimation; nonparametric regression},
language = {eng},
issn = {0943-4062},
journal = {Computational Statistics},
title = {Plug-in method for nonparametric regression},
volume = {2008},
year = {2008}
}
TY - JOUR
ID - 634140
AU - Koláček, Jan
PY - 2008
TI - Plug-in method for nonparametric regression
JF - Computational Statistics
VL - 2008
IS - 1
SP - 63-78
EP - 63-78
PB - Physica-Verlag
SN - 09434062
KW - bandwidth selection
KW - Fourier transform
KW - kernel estimation
KW - nonparametric regression
N2 - The problem of bandwidth selection for non-parametric kernel regression is considered. We will follow the Nadaraya -- Watson and local linear estimator 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. As a result of this procedure, we obtain an estimation of unknown parameters of average mean square error function (AMSE). This process is known as a plug-in method. Simulation studies suggest that the plug-in method could have preferable properties to the classical one.
ER -
KOLÁČEK, Jan. Plug-in method for nonparametric regression. \textit{Computational Statistics}. Germany: Physica-Verlag, 2008, vol.~2008, No~1, p.~63-78. ISSN~0943-4062.
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