Fourier analysis of serial dependence measures

dc.contributor.author	Van Hecke, Ria
dc.contributor.author	Volgushev, Stanislav
dc.contributor.author	Dette, Holger
dc.date.accessioned	2017-03-15T11:40:32Z
dc.date.available	2017-03-15T11:40:32Z
dc.date.issued	2017
dc.description.abstract	Classical spectral analysis is based on the discrete Fourier transform of the auto-covariances. In this paper we investigate the asymptotic properties of new frequency domain methods where the auto-covariances in the spectral density are replaced by alternative dependence measures which can be estimated by U-statistics. An interesting example is given by Kendall's r , for which the limiting variance exhibits a surprising behavior.	en
dc.identifier.uri	http://hdl.handle.net/2003/35853
dc.identifier.uri	http://dx.doi.org/10.17877/DE290R-17877
dc.language.iso	en	de
dc.relation.ispartofseries	Discussion Paper / SFB823;6, 2017	en
dc.subject	spectral theory	en
dc.subject	U-statistics	en
dc.subject	strictly stationary time series	en
dc.subject.ddc	310
dc.subject.ddc	330
dc.subject.ddc	620
dc.subject.rswk	Spektraldichte	de
dc.subject.rswk	U-Statistik	de
dc.title	Fourier analysis of serial dependence measures	en
dc.type	Text	de
dc.type.publicationtype	workingPaper	de
dcterms.accessRights	open access

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