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...

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Bibliographic Details
Main Authors: Franke, Jürgen (Author) , Kreiß, Jens-Peter (Author) , Mammen, Enno (Author)
Format: Article (Journal)
Language:English
Published: 2002
In: Bernoulli
Year: 2002, Volume: 8, Issue: 1, Pages: 1-37
ISSN:1573-9759
Online Access:Verlag, Volltext: http://www.jstor.org/stable/3318641
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Author Notes:Jürgen Franke, Jens-Peter Kreiss, Enno Mammen
Description
Summary: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.
Item Description:Gesehen am 05.02.2018
Physical Description:Online Resource
ISSN:1573-9759