Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Enache, Daniel | de |
dc.contributor.author | Weihs, Claus | de |
dc.date.accessioned | 2005-01-31T08:15:05Z | - |
dc.date.available | 2005-01-31T08:15:05Z | - |
dc.date.issued | 2004 | de |
dc.identifier.uri | http://hdl.handle.net/2003/20080 | - |
dc.identifier.uri | http://dx.doi.org/10.17877/DE290R-2762 | - |
dc.description.abstract | When trying to interpret estimated parameters the researcher is interested in the (relative) importance of the individual predictors. However, if the predictors are highly correlated, the interpretation of coefficients, e.g. as economic "multipliers", is not applicable in standard regression or classification models. The goal of this paper is to develop a procedure to obtain such measures of importance for classification methods and to apply them to models for the classification of german business cycle phases. | en |
dc.format.extent | 112421 bytes | - |
dc.format.mimetype | application/pdf | - |
dc.language.iso | en | de |
dc.publisher | Universität Dortmund | de |
dc.subject.ddc | 310 | de |
dc.title | Importance Assessment of Correlated Predictors in Business Cycles Classification | en |
dc.type | Text | de |
dc.type.publicationtype | report | en |
dcterms.accessRights | open access | - |
Appears in Collections: | Sonderforschungsbereich (SFB) 475 |
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