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More efficient local polynomial estimation in nonparametric regression with autocorrelated errors

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We propose a modification of local polynomial time series regression estimators that improves efficiency when the innovation process is autocorrelated. The procedure is based on a pre-whitening transformation of the dependent variable that must be estimated from the data. We establish the asymptotic...

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Hauptverfasser: Xiao, Zhijie (VerfasserIn) , Linton, Oliver (VerfasserIn) , Carroll, Raymond J. (VerfasserIn) , Mammen, Enno (VerfasserIn)
Dokumenttyp: Article (Journal)
Sprache:Englisch
Veröffentlicht: Dec 2003
In: Journal of the American Statistical Association
Year: 2003, Jahrgang: 98, Heft: 464, Pages: 980-992
ISSN:1537-274X
Online-Zugang:Verlag, Volltext: http://www.jstor.org/stable/30045344
Verlag, Volltext: http://www.jstor.org/stable/pdf/30045344.pdf?refreqid=excelsior:79050497e35fe71e5daeb922943c729f
Volltext
Verfasserangaben:Zhijie Xiao, Oliver B. Linton, Raymond J. Carroll, Enno Mammen

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