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Statements

Subject Item
n2:RIV%2F00216224%3A14310%2F05%3A00013348%21RIV10-GA0-14310___
rdf:type
skos:Concept n13:Vysledek
dcterms:description
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. 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.
dcterms:title
Bandwidth selection for nonparametric regression - plug-in method Bandwidth selection for nonparametric regression - plug-in method
skos:prefLabel
Bandwidth selection for nonparametric regression - plug-in method Bandwidth selection for nonparametric regression - plug-in method
skos:notation
RIV/00216224:14310/05:00013348!RIV10-GA0-14310___
n3:aktivita
n4:P
n3:aktivity
P(GA402/04/1308)
n3:dodaniDat
n12:2010
n3:domaciTvurceVysledku
n5:3062023
n3:druhVysledku
n14:O
n3:duvernostUdaju
n9:S
n3:entitaPredkladatele
n7:predkladatel
n3:idSjednocenehoVysledku
513506
n3:idVysledku
RIV/00216224:14310/05:00013348
n3:jazykVysledku
n11:eng
n3:klicovaSlova
bandwidth selection; Fourier transform; kernel estimation; nonparametric regression
n3:klicoveSlovo
n10:Fourier%20transform n10:bandwidth%20selection n10:nonparametric%20regression n10:kernel%20estimation
n3:kontrolniKodProRIV
[5E7F4CC6074A]
n3:obor
n15:BA
n3:pocetDomacichTvurcuVysledku
1
n3:pocetTvurcuVysledku
1
n3:projekt
n16:GA402%2F04%2F1308
n3:rokUplatneniVysledku
n12:2005
n3:tvurceVysledku
Koláček, Jan
n17:organizacniJednotka
14310