Bootstrap of kernel smoothing in nonlinear time series

Kernel smoothing in nonparametric autoregressive schemes offers a powerful tool in modelling time series. We show that the bootstrap can be used for estimating the distribution of kernel smoothers. This can be done by mimicking the stochastic nature of the whole process in the bootstrap resample or...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: Franke, Jürgen (VerfasserIn) , Kreiß, Jens-Peter (VerfasserIn) , Mammen, Enno (VerfasserIn)
Dokumenttyp: Article (Journal)
Sprache:Englisch
Veröffentlicht: 2002
In: Bernoulli
Year: 2002, Jahrgang: 8, Heft: 1, Pages: 1-37
ISSN:1573-9759
Online-Zugang:Verlag, Volltext: http://www.jstor.org/stable/3318641
Volltext
Verfasserangaben:Jürgen Franke, Jens-Peter Kreiss, Enno Mammen
Beschreibung
Zusammenfassung:Kernel smoothing in nonparametric autoregressive schemes offers a powerful tool in modelling time series. We show that the bootstrap can be used for estimating the distribution of kernel smoothers. This can be done by mimicking the stochastic nature of the whole process in the bootstrap resample or by generating a simple regression model. Consistency of these bootstrap procedures will be shown.
Beschreibung:Gesehen am 05.02.2018
Beschreibung:Online Resource
ISSN:1573-9759