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@inbook{1113536,
author = {Lajdová, Dagmar and Koláček, Jan and Horová, Ivanka},
address = {Athens},
booktitle = {Theoretical and Applied Issues in Statistics and Demography},
editor = {C H Skiadas},
keywords = {kernel; regression; bandwidth selection; correlated errors},
howpublished = {tištěná verze "print"},
language = {eng},
location = {Athens},
isbn = {978-618-81257-7-3},
pages = {3-14},
publisher = {International Society for the Advancement of Science and Technology (ISAST)},
title = {Kernel Regression Model with Correlated Errors},
year = {2014}
}
TY - CHAP
ID - 1113536
AU - Lajdová, Dagmar - Koláček, Jan - Horová, Ivanka
PY - 2014
TI - Kernel Regression Model with Correlated Errors
VL - Neuveden
PB - International Society for the Advancement of Science and Technology (ISAST)
CY - Athens
SN - 9786188125773
KW - kernel
KW - regression
KW - bandwidth selection
KW - correlated errors
N2 - Kernel regression is one of the commonly used nonparametric methods for an estimation of a regression function. Nevertheless, there is a problem of choosing the value of the smoothing parameter, the bandwidth. In the case of independent observations the literature on the bandwidth selection is quite extensive. However, these standard methods, like cross-validation, perform badly when the errors are correlated. There are several possibilities how to overcome this. We will present and compare the partitioned cross-validation method and the plug-in method.
ER -
LAJDOVÁ, Dagmar, Jan KOLÁČEK and Ivanka HOROVÁ. Kernel Regression Model with Correlated Errors. In C H Skiadas. \textit{Theoretical and Applied Issues in Statistics and Demography}. Athens: International Society for the Advancement of Science and Technology (ISAST), 2014, p.~3-14. ISBN~978-618-81257-7-3.
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