Detecting deviations from second-order stationarity in locally stationary functional time series

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dc.contributor.authorBücher, Axel
dc.contributor.authorDette, Holger
dc.contributor.authorHeinrichs, Florian
dc.date.accessioned2018-09-05T09:38:49Z
dc.date.available2018-09-05T09:38:49Z
dc.date.issued2018
dc.description.abstractA time-domain test for the assumption of second order stationarity of a functional time series is proposed. The test is based on combining individual cumulative sum tests which are designed to be sensitive to changes in the mean, variance and autocovariance operators, respectively. The combination of their dependent p-values relies on a joint dependent block multiplier bootstrap of the individual test statistics. Conditions under which the proposed combined testing procedure is asymptotically valid under stationarity are provided. A procedure is proposed to automatically choose the block length parameter needed for the construction of the bootstrap. The finitesample behavior of the proposed test is investigated in Monte Carlo experiments and an illustration on a real data set is provided.en
dc.identifier.urihttp://hdl.handle.net/2003/37118
dc.identifier.urihttp://dx.doi.org/10.17877/DE290R-19114
dc.language.isoende
dc.relation.ispartofseriesDiscussion Paper / SFB823;17/2018
dc.subjectalpha-mixingen
dc.subjectchange pointsen
dc.subjectblock multiplier bootstrapen
dc.subjectauto-covariance operatoren
dc.subjectCUSUM-testen
dc.subject.ddc310
dc.subject.ddc330
dc.subject.ddc620
dc.titleDetecting deviations from second-order stationarity in locally stationary functional time seriesen
dc.typeTextde
dc.type.publicationtypeworkingPaperde
dcterms.accessRightsopen access
eldorado.secondarypublicationfalsede

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