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dc.contributor.authorTrenkler, Götzde
dc.contributor.authorTroschke, Sven-Oliverde
dc.date.accessioned2004-12-06T18:44:22Z-
dc.date.available2004-12-06T18:44:22Z-
dc.date.issued2000de
dc.identifier.urihttp://hdl.handle.net/2003/5084-
dc.identifier.urihttp://dx.doi.org/10.17877/DE290R-5428-
dc.description.abstractIn Troschke and Trenkler (2000) the authors introduce linear plus quadratic approaches to the mean square error optimal combination of forecasts for a scalar random variable. In this paper it is shown how the optimal combination parameters can be obtained with the help of linear regression. Thus numerical considerations as well as application of linear plus quadratic combination to empirical data are facilitated. First results on the comparison of the new methods to the classical linear approaches are given. It is found that there are situations where the linear plus quadratic approaches may be employed beneficially, but further investigations have to be carried out.en
dc.format.extent241329 bytes-
dc.format.extent312129 bytes-
dc.format.mimetypeapplication/pdf-
dc.format.mimetypeapplication/postscript-
dc.language.isoende
dc.publisherUniversitätsbibliothek Dortmundde
dc.subjectcombination of forecastsen
dc.subjectlinear plus quadratic combinationen
dc.subjectlinear regressionen
dc.subject.ddc310de
dc.titleRegression Approach to the Linear Plus Quadratic Combination of Forecastsen
dc.typeTextde
dc.type.publicationtypereporten
dcterms.accessRightsopen access-
Appears in Collections:Sonderforschungsbereich (SFB) 475

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