Authors: Lübke, Karsten
Weihs, Claus
Title: A Note on the Dimension of the Projection Space in a Latent Factor Regression Model with Application to Business Cycle Classification
Language (ISO): en
Abstract: In this paper it is shown that the number of latent factors in a multiple multivariate regression model need not be larger than the number of the response variables in order to achieve an optimal prediction. The practical importance of this lemma is outlined and an application of such a projection on latent factors in a classification example is given.
Subject Headings: latent factor models
projection matrix
regression
classification
URI: http://hdl.handle.net/2003/4900
http://dx.doi.org/10.17877/DE290R-15078
Issue Date: 2004
Publisher: Universitätsbibliothek Dortmund
Appears in Collections:Sonderforschungsbereich (SFB) 475

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