Hits-and-misses for the evaluation and combination of forecasts

dc.contributor.author	Wenzel, Thomas	de
dc.date.accessioned	2004-12-06T18:42:29Z
dc.date.available	2004-12-06T18:42:29Z
dc.date.issued	2000	de
dc.description.abstract	Error measures for the evaluation of forecasts are usually based on the size of the forecast errors. Common measures are e.g. the Mean Squared Error (MSE), the Mean Absolute Deviation (MAD) or the Mean Absolute Percentage Error (MAPE). Alternative measures for the comparison of forecasts are turning points or hits-and-misses, where an indicator loss function is used to decide, if a forecast is of high quality or not. Here, we discuss the latter to obtain reliable combined forecasts.	en
dc.format.extent	580473 bytes
dc.format.extent	79190 bytes
dc.format.mimetype	application/pdf
dc.format.mimetype	application/postscript
dc.identifier.uri	http://hdl.handle.net/2003/5031
dc.identifier.uri	http://dx.doi.org/10.17877/DE290R-5380
dc.language.iso	en	de
dc.publisher	Universitätsbibliothek Dortmund	de
dc.subject	combination of forecasts	en
dc.subject	fuzzy	en
dc.subject	hits-and-misses	en
dc.subject	turning points	en
dc.subject.ddc	310	de
dc.title	Hits-and-misses for the evaluation and combination of forecasts	en
dc.type	Text	de
dc.type.publicationtype	report	en
dcterms.accessRights	open access

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