A portmanteau-type test for detecting serial correlation in locally stationary functional time series

dc.contributor.author	Bücher, Axel
dc.contributor.author	Dette, Holger
dc.contributor.author	Heinrichs, Florian
dc.date.accessioned	2020-09-22T11:10:15Z
dc.date.available	2020-09-22T11:10:15Z
dc.date.issued	2020
dc.description.abstract	The Portmanteau test provides the vanilla method for detecting serial correlations in classical univariate time series analysis. The method is extended to the case of observations from a locally stationary functional time series. Asymptotic critical values are obtained by a suitable block multiplier bootstrap procedure. The test is shown to asymptotically hold its level and to be consistent against general alternatives.	en
dc.identifier.uri	http://hdl.handle.net/2003/39304
dc.identifier.uri	http://dx.doi.org/10.17877/DE290R-21205
dc.language.iso	en	de
dc.relation.ispartofseries	Discussion Paper / SFB823;25/2020
dc.subject	autocovariance operator	en
dc.subject	time domain test	en
dc.subject	functional white noise	en
dc.subject	block multiplier bootstrap	en
dc.subject.ddc	310
dc.subject.ddc	330
dc.subject.ddc	620
dc.subject.rswk	Zeitreihenanalyse	de
dc.subject.rswk	Weißes Rauschen	de
dc.subject.rswk	Bootstrap-Statistik	de
dc.title	A portmanteau-type test for detecting serial correlation in locally stationary functional time series	en
dc.type	Text	de
dc.type.publicationtype	workingPaper	de
dcterms.accessRights	open access
eldorado.secondarypublication	false	de

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