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1997-07-30Buch DOI: 10.18452/3804
Bootstrap of kernel smoothing in nonlinear time series
dc.contributor.authorFranke, Jürgen
dc.contributor.authorKreiss, Jens-Peter
dc.contributor.authorMammen, Enno
dc.date.accessioned2017-06-15T22:10:31Z
dc.date.available2017-06-15T22:10:31Z
dc.date.created2006-06-01
dc.date.issued1997-07-30
dc.identifier.issn1436-1086
dc.identifier.urihttp://edoc.hu-berlin.de/18452/4456
dc.description.abstractKernel 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.eng
dc.language.isoeng
dc.publisherHumboldt-Universität zu Berlin, Wirtschaftswissenschaftliche Fakultät
dc.subject.ddc330 Wirtschaft
dc.titleBootstrap of kernel smoothing in nonlinear time series
dc.typebook
dc.identifier.urnurn:nbn:de:kobv:11-10064067
dc.identifier.doihttp://dx.doi.org/10.18452/3804
dc.subject.dnb17 Wirtschaft
local.edoc.container-titleSonderforschungsbereich 373: Quantification and Simulation of Economic Processes
local.edoc.pages37
local.edoc.type-nameBuch
local.edoc.container-typeseries
local.edoc.container-type-nameSchriftenreihe
local.edoc.container-volume1997
local.edoc.container-issue20
local.edoc.container-year1997
local.edoc.container-erstkatid2135319-0

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