The shrinkage approach in the combination of forecasts

dc.contributor.author	Wenzel, Thomas	de
dc.date.accessioned	2004-12-06T18:43:16Z
dc.date.available	2004-12-06T18:43:16Z
dc.date.issued	2000	de
dc.description.abstract	An 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.extent	141252 bytes
dc.format.extent	826293 bytes
dc.format.mimetype	application/pdf
dc.format.mimetype	application/postscript
dc.identifier.uri	http://hdl.handle.net/2003/5054
dc.identifier.uri	http://dx.doi.org/10.17877/DE290R-15131
dc.language.iso	en	de
dc.publisher	Universitätsbibliothek Dortmund	de
dc.subject	combination of forecast	en
dc.subject	mean squared error	en
dc.subject	shrinkage	en
dc.subject.ddc	310	de
dc.title	The shrinkage approach in the combination of forecasts	en
dc.type	Text	de
dc.type.publicationtype	report	en
dcterms.accessRights	open access

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