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dc.contributor.authorBücher, Axel-
dc.contributor.authorDette, Holger-
dc.contributor.authorHeinrichs, Florian-
dc.date.accessioned2020-09-22T11:10:15Z-
dc.date.available2020-09-22T11:10:15Z-
dc.date.issued2020-
dc.identifier.urihttp://hdl.handle.net/2003/39304-
dc.identifier.urihttp://dx.doi.org/10.17877/DE290R-21205-
dc.description.abstractThe 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.language.isoende
dc.relation.ispartofseriesDiscussion Paper / SFB823;25/2020-
dc.subjectautocovariance operatoren
dc.subjecttime domain testen
dc.subjectfunctional white noiseen
dc.subjectblock multiplier bootstrapen
dc.subject.ddc310-
dc.subject.ddc330-
dc.subject.ddc620-
dc.titleA portmanteau-type test for detecting serial correlation in locally stationary functional time seriesen
dc.typeTextde
dc.type.publicationtypeworkingPaperde
dc.subject.rswkZeitreihenanalysede
dc.subject.rswkWeißes Rauschende
dc.subject.rswkBootstrap-Statistikde
dcterms.accessRightsopen access-
eldorado.secondarypublicationfalsede
Appears in Collections:Sonderforschungsbereich (SFB) 823

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