Analyzing associations in multivariate binary time series

dc.contributor.authorFried, Roland
dc.contributor.authorKuhls, Silvia
dc.contributor.authorMolina, Isabel
dc.date.accessioned2006-03-16T14:35:47Z
dc.date.available2006-03-16T14:35:47Z
dc.date.issued2006-03-16T14:35:47Z
dc.description.abstractWe analyze multivariate binary time series using a mixed parameterization in terms of the conditional expectations given the past and the pairwise canonical interactions among contemporaneous variables. This allows consistent inference on the influence of past variables even if the contemporaneous associations are misspecified. Particularly, we can detect and test Granger nonĀ­-causalities since they correspond to zero parameter values.en
dc.format.extent103844 bytes
dc.format.extent222753 bytes
dc.format.mimetypeapplication/pdf
dc.format.mimetypeapplication/postscript
dc.identifier.urihttp://hdl.handle.net/2003/22242
dc.identifier.urihttp://dx.doi.org/10.17877/DE290R-14323
dc.language.isoen
dc.subjectCanonical interactionen
dc.subjectGranger non-causalitiesen
dc.subjectMixed parameterizationen
dc.subjectZero parameter valuesen
dc.subject.ddc004
dc.titleAnalyzing associations in multivariate binary time seriesen
dc.typeTextde
dc.type.publicationtypereporten
dcterms.accessRightsopen access

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