Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/22541
Authors: 
Weihs, Claus
Luebke, Karsten
Year of Publication: 
2004
Series/Report no.: 
Technical Report / Universität Dortmund, SFB 475 Komplexitätsreduktion in Multivariaten Datenstrukturen 2004,29
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.
Subjects: 
Latent Factor Models
Projection Matrix
Regression
Classification
Document Type: 
Working Paper

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