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A note on the general solution for a projection matrix in latent factor models
Groß, Jürgen; Lübke, Karsten; Weihs, Claus - 2002
Persistent link: https://www.econbiz.de/10009772061
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A Note on the Dimension of the Projection Space in a Latent Factor Regression Model with Application to Business Cycle Classification
Weihs, Claus; Luebke, Karsten - 2004
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...
Persistent link: https://www.econbiz.de/10010296612
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A Note on the Dimension of the Projection Space in a Latent Factor Regression Model with Application to Business Cycle Classification
Weihs, Claus; Luebke, Karsten - Institut für Wirtschafts- und Sozialstatistik, … - 2004
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...
Persistent link: https://www.econbiz.de/10009216883