Latent factor prediction pursuit for rank deficient regressors

In simulation studies Latent Factor Prediction Pursuit outperformed classical reduced rank regression methods. The algorithm described so far for Latent Factor Prediction Pursuit had two shortcomings: It was only implemented for situations where the explanatory variables were of full colum rank. Als...

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Bibliographische Detailangaben
1. Verfasser: Luebke, Karsten (VerfasserIn)
Weitere Verfasser: Czogiel, Irina (VerfasserIn), Weihs, Claus (VerfasserIn)
Format: UnknownFormat
Sprache:eng
Veröffentlicht: 2004
Schriftenreihe:Technical Report / Sonderforschungsbereich 475, Komplexitätsreduktion in Multivariaten Datenstrukturen, Universität Dortmund 2004,75
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Zusammenfassung:In simulation studies Latent Factor Prediction Pursuit outperformed classical reduced rank regression methods. The algorithm described so far for Latent Factor Prediction Pursuit had two shortcomings: It was only implemented for situations where the explanatory variables were of full colum rank. Also instead of the projection matrix only the regression matrix was calculated. These problems are addressed by a new algorithm which finds the prediction optimal projection.
Beschreibung:Internetausg.: http://www.sfb475.uni-dortmund.de/berichte/tr75-04.pdf
Beschreibung:17 S
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