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Statements

Subject Item
n2:RIV%2F00216224%3A14310%2F03%3A00021253%21RIV08-MSM-14310___
rdf:type
skos:Concept n16:Vysledek
dcterms:description
Práce se zabývá některými metodami pro výběr optimální šířky okna při neparametrické regresi. The problem of bandwidth selection for nonparametric kernel regression is considered. It is well recognized that the classical bandwidth selectors are subject to large sample variation. Due to the large variation, these selectors might not be very useful in practice. Most of bandwidth selectors are based on the residual sum of squares (RSS), the source of the variation is pointed out. The observation leads to consideration of a procedure which stabilizes the RSS by modifying the periodogram of the observations. We will follow the Nadaraya - Watson estimators especially. In a simulation study, it is confirmed that the stabilized bandwidth selectors perform much better than the classical selectors. The problem of bandwidth selection for nonparametric kernel regression is considered. It is well recognized that the classical bandwidth selectors are subject to large sample variation. Due to the large variation, these selectors might not be very useful in practice. Most of bandwidth selectors are based on the residual sum of squares (RSS), the source of the variation is pointed out. The observation leads to consideration of a procedure which stabilizes the RSS by modifying the periodogram of the observations. We will follow the Nadaraya - Watson estimators especially. In a simulation study, it is confirmed that the stabilized bandwidth selectors perform much better than the classical selectors.
dcterms:title
Stabilizační metody pro hledání optimální šířky okna pro neparametrickou regresi Some stabilized bandwidth selectors for nonparametric regression Some stabilized bandwidth selectors for nonparametric regression
skos:prefLabel
Some stabilized bandwidth selectors for nonparametric regression Stabilizační metody pro hledání optimální šířky okna pro neparametrickou regresi Some stabilized bandwidth selectors for nonparametric regression
skos:notation
RIV/00216224:14310/03:00021253!RIV08-MSM-14310___
n3:strany
65-68
n3:aktivita
n15:Z
n3:aktivity
Z(MSM 143100001)
n3:cisloPeriodika
12
n3:dodaniDat
n6:2008
n3:domaciTvurceVysledku
n7:3062023
n3:druhVysledku
n8:J
n3:duvernostUdaju
n12:S
n3:entitaPredkladatele
n10:predkladatel
n3:idSjednocenehoVysledku
627795
n3:idVysledku
RIV/00216224:14310/03:00021253
n3:jazykVysledku
n18:eng
n3:klicovaSlova
Kernel regression; bandwidth selector; Nadaraya - Watson estimators; periodogram
n3:klicoveSlovo
n4:Nadaraya n4:bandwidth%20selector n4:periodogram n4:Kernel%20regression
n3:kodStatuVydavatele
SK - Slovenská republika
n3:kontrolniKodProRIV
[B475747A037B]
n3:nazevZdroje
Journal of Electrical Engineering
n3:obor
n14:BB
n3:pocetDomacichTvurcuVysledku
1
n3:pocetTvurcuVysledku
1
n3:rokUplatneniVysledku
n6:2003
n3:svazekPeriodika
54
n3:tvurceVysledku
Koláček, Jan
n3:zamer
n17:MSM%20143100001
s:issn
1335-3632
s:numberOfPages
4
n9:organizacniJednotka
14310