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@proceedings{634143,
author = {Koláček, Jan},
booktitle = {Programme and Abstracts, IASC 3rd World Conference on CSDA},
keywords = {bandwidth selection; Fourier transform; kernel estimation; nonparametric regression},
language = {eng},
title = {Bandwidth selection for nonparametric regression - plug-in method},
year = {2005}
}
TY - CONF
ID - 634143
AU - Koláček, Jan
PY - 2005
TI - Bandwidth selection for nonparametric regression - plug-in method
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. Bandwidth selection for nonparametric regression - plug-in method. In \textit{Programme and Abstracts, IASC 3rd World Conference on CSDA}. 2005.
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