The shrinkage approach in the combination of forecasts

dc.contributor.authorWenzel, Thomasde
dc.date.accessioned2004-12-06T18:43:16Z
dc.date.available2004-12-06T18:43:16Z
dc.date.issued2000de
dc.description.abstractAn unbiased point estimator T for an unknown parameter q can be improved in the sense of the Mean Squared Error (MSE) by T T l= l for suitable factors l. Here, we want to discuss this approach in the context of combination of forecasts. We consider the shrinkage technique for unbiased univariate and multivariate forecast combinations. In the univariate case our aim is to reduce the MSE. In the multivariate case we want to improve unbiased forecast combinations in the sense of the Scalar Mean Squared Error (SMSE) or the Matrix Mean Squared Error (MMSE).en
dc.format.extent141252 bytes
dc.format.extent826293 bytes
dc.format.mimetypeapplication/pdf
dc.format.mimetypeapplication/postscript
dc.identifier.urihttp://hdl.handle.net/2003/5054
dc.identifier.urihttp://dx.doi.org/10.17877/DE290R-15131
dc.language.isoende
dc.publisherUniversitätsbibliothek Dortmundde
dc.subjectcombination of forecasten
dc.subjectmean squared erroren
dc.subjectshrinkageen
dc.subject.ddc310de
dc.titleThe shrinkage approach in the combination of forecastsen
dc.typeTextde
dc.type.publicationtypereporten
dcterms.accessRightsopen access
eldorado.dnb.deposittrue

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