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@article{1123280,
author = {Koláček, Jan and Horová, Ivanka},
article_number = {5},
doi = {http://dx.doi.org/10.1080/03610926.2013.864770},
keywords = {kernel regression; bandwidth selection; iterative method},
language = {eng},
issn = {0361-0926},
journal = {Communications in Statistics - Theory and Methods},
title = {Selection of bandwidth for kernel regression},
volume = {45},
year = {2016}
}
TY - JOUR
ID - 1123280
AU - Koláček, Jan - Horová, Ivanka
PY - 2016
TI - Selection of bandwidth for kernel regression
JF - Communications in Statistics - Theory and Methods
VL - 45
IS - 5
SP - 1487-1500
EP - 1487-1500
PB - Marcel Dekker
SN - 03610926
KW - kernel regression
KW - bandwidth selection
KW - iterative method
N2 - The most important factor in kernel regression is a choice of a bandwidth. Considerable attention has been paid to extension the idea of an iterative method known for a kernel density estimate to kernel regression. Data-driven selectors of the bandwidth for kernel regression are considered. The proposed method is based on an optimally balanced relation between the integrated variance and the integrated square bias. This approach leads to an iterative quadratically convergent process. The analysis of statistical properties shows the rationale of the proposed method. In order to see statistical properties of this method the consistency is determined. The utility of the method is illustrated through a simulation study and real data applications.
ER -
KOLÁČEK, Jan and Ivanka HOROVÁ. Selection of bandwidth for kernel regression. \textit{Communications in Statistics - Theory and Methods}. Marcel Dekker, 2016, vol.~45, No~5, p.~1487-1500. ISSN~0361-0926. Available from: https://dx.doi.org/10.1080/03610926.2013.864770.
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