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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Year of publication:	1997
Authors:	Franke, Jürgen ; Kreiss, Jens-Peter ; Mammen, Enno
Publisher:	Berlin : Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes

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Series:	SFB 373 Discussion Paper ; 1997,20
Type of publication:	Book / Working Paper
Type of publication (narrower categories):	Working Paper
Language:	English
Other identifiers:	728568683 [GVK] hdl:10419/66303 [Handle] RePEc:zbw:sfb373:199720 [RePEc]
Source:	EconStor

Persistent link: https://www.econbiz.de/10010310821