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dc.contributor.authorFried, Rolanden_US
dc.contributor.authorDidelez, Vanessaen_US
dc.date.accessioned2011-09-06T11:45:19Z-
dc.date.available2011-09-06T11:45:19Z-
dc.date.issued2003en_US
dc.identifier.urihttp://hdl.handle.net/10419/49370-
dc.description.abstractWe investigate the possibility of exploiting partial correlation graphs for identifying interpretable latent variables underlying a multivariate time series. It is shown how the collapsibility and separation properties of partial correlation graphs can be used to understand the relation between a factor model and the structure among the observable variables.en_US
dc.language.isoengen_US
dc.publisherUniv., SFB 475 Dortmunden_US
dc.relation.ispartofseriesTechnical Report // Universität Dortmund, SFB 475 Komplexitätsreduktion in Multivariaten Datenstrukturen 2003,06en_US
dc.subject.ddc310en_US
dc.subject.keywordTime series analysisen
dc.subject.keywordDimension reductionen
dc.subject.keywordFactor analysisen
dc.subject.keywordPartial correlationsen
dc.subject.stwMultivariate Analyseen_US
dc.subject.stwZeitreihenanalyseen_US
dc.subject.stwTheorieen_US
dc.subject.stwKorrelationen_US
dc.titleLatent variable analysis and partial correlation graphs for multivariate time seriesen_US
dc.typeWorking Paperen_US
dc.identifier.ppn36986025Xen_US
dc.rightshttp://www.econstor.eu/dspace/Nutzungsbedingungenen_US
dc.identifier.repecRePEc:zbw:sfb475:200306-
Appears in Collections:Technical Reports, SFB 475, TU Dortmund

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