Bootstrap of kernel smoothing in nonlinear time series

  • Kernel smoothing in nonparametric autoregressive schemes offers a powerful tool in modelling time series. In this paper it is shown 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 resampling or by generating a simple regression model. Consistency of these bootstrap procedures will be shown.

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Metadaten
Author:Jürgen Franke, Kreiss J.-P., E. Mammen
URN (permanent link):urn:nbn:de:hbz:386-kluedo-4640
Serie (Series number):Report in Wirtschaftsmathematik (WIMA Report) (22)
Document Type:Preprint
Language of publication:English
Year of Completion:1999
Year of Publication:1999
Publishing Institute:Technische Universität Kaiserslautern
Faculties / Organisational entities:Fachbereich Mathematik
DDC-Cassification:510 Mathematik

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