Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/32166
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dc.contributor.authorBeran, Janen_US
dc.date.accessioned2009-09-17en_US
dc.date.accessioned2010-05-14T12:00:36Z-
dc.date.available2010-05-14T12:00:36Z-
dc.date.issued2008en_US
dc.identifier.piurn:nbn:de:bsz:352-opus-116724-
dc.identifier.urihttp://hdl.handle.net/10419/32166-
dc.description.abstractWe consider dependence structures in multivariate time series that are characterized by deterministic trends. Results from spectral analysis for stationary processes are extended to deterministic trend functions. A regression cross covariance and spectrum are defined. Estimation of these quantities is based on wavelet thresholding. The method is illustrated by a simulated example and a three-dimensional time series consisting of ECG, blood pressure and cardiac stroke volume measurements.en_US
dc.language.isoengen_US
dc.publisher|aCoFE |cKonstanzen_US
dc.relation.ispartofseries|aDiscussion paper series // Zentrum für Finanzen und Ökonometrie, Universität Konstanz |x2008,01en_US
dc.subject.ddc330en_US
dc.subject.keywordNonparametric trend estimationen_US
dc.subject.keywordcross spectrumen_US
dc.subject.keywordwaveletsen_US
dc.subject.keywordregression spectrumen_US
dc.subject.keywordphaseen_US
dc.subject.keywordthreshold estimatoren_US
dc.titleA nonparametric regression cross spectrum for multivariate time seriesen_US
dc.type|aWorking Paperen_US
dc.identifier.ppn608950947en_US
dc.rightshttp://www.econstor.eu/dspace/Nutzungsbedingungen-

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