Full metadata record
DC FieldValueLanguage
dc.contributor.authorWenzel, Thomasde
dc.date.accessioned2004-12-06T18:43:16Z-
dc.date.available2004-12-06T18:43:16Z-
dc.date.issued2000de
dc.identifier.urihttp://hdl.handle.net/2003/5054-
dc.identifier.urihttp://dx.doi.org/10.17877/DE290R-15131-
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.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-
Appears in Collections:Sonderforschungsbereich (SFB) 475

Files in This Item:
File Description SizeFormat 
2000_44.pdfDNB137.94 kBAdobe PDFView/Open
tr44-00.ps806.93 kBPostscriptView/Open


This item is protected by original copyright



This item is protected by original copyright rightsstatements.org