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dc.contributor.authorSchüle, Martin-
dc.contributor.authorOtt, Thomas-
dc.contributor.authorSchwendner, Peter-
dc.date.accessioned2018-11-22T15:03:32Z-
dc.date.available2018-11-22T15:03:32Z-
dc.date.issued2016-
dc.identifier.urihttps://digitalcollection.zhaw.ch/handle/11475/13153-
dc.description.abstractOften the signature of a complex system is a couple of empirically found time series. As the exact processes generating these series are often unknown, one contents oneself with mere data analysis, i.e., an analysis of the statistical features of the time series. Beyond the individual statistical characteristics of the time series, a key tool to investigate the structural behaviour of the complex system is considering the correlation structure, i.e. the system of pairwise correlations between the time series.de_CH
dc.language.isoende_CH
dc.publisherIEICEde_CH
dc.rightsLicence according to publishing contractde_CH
dc.subjectComplex systemsde_CH
dc.subjectForecastingde_CH
dc.subjectEconometricsde_CH
dc.subject.ddc500: Naturwissenschaften und Mathematikde_CH
dc.titleForecasting correlation structuresde_CH
dc.typeKonferenz: Paperde_CH
dcterms.typeTextde_CH
zhaw.departementSchool of Management and Lawde_CH
zhaw.organisationalunitInstitut für Angewandte Simulation (IAS)de_CH
zhaw.conference.details2016 International Symposium on Nonlinear Theory and Its Applications (NOLTA2016), Yugawara, Japan, 27-30 November 2016de_CH
zhaw.funding.euNode_CH
zhaw.originated.zhawYesde_CH
zhaw.publication.statuspublishedVersionde_CH
zhaw.publication.reviewPeer review (Abstract)de_CH
zhaw.title.proceedingsProceedings of the 2016 international symposium on nonlinear theory and its applicationsde_CH
zhaw.webfeedBio-Inspired Modelling and Learning Systemsde_CH
Appears in Collections:Publikationen School of Management and Law

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