Authors: | Czogiel, I. Luebke, K. Weihs, C. |
Title: | Latent Factor Prediction Pursuit for Rank Deficient Regressors |
Language (ISO): | en |
Abstract: | 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. |
URI: | http://hdl.handle.net/2003/20089 http://dx.doi.org/10.17877/DE290R-15681 |
Issue Date: | 2004 |
Provenance: | Universität Dortmund |
Appears in Collections: | Sonderforschungsbereich (SFB) 475 |
This item is protected by original copyright |
Items in Eldorado are protected by copyright, with all rights reserved, unless otherwise indicated.