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Robust dimension reduction methods for regression and discriminant analysis are implemented that yield estimates with a partial least squares alike interpretability. Partial robust M regression (PRM) is robust to both vertical outliers and leverage points. Sparse partial robust M regression (SPRM) is a related robust method with sparse coefficient estimate, and therefore with intrinsic variable selection. For binary classification related discriminant methods are PRM-DA and SPRM-DA.
Package details |
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Author | Sven Serneels (BASF Corp) and Irene Hoffmann |
Maintainer | Irene Hoffmann <irene.hoffmann@tuwien.ac.at> |
License | GPL (>= 3) |
Version | 1.2.2 |
Package repository | View on CRAN |
Installation |
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