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.
|Author||Sven Serneels (BASF Corp) and Irene Hoffmann|
|Maintainer||Irene Hoffmann <[email protected]>|
|License||GPL (>= 3)|
|Package repository||View on CRAN|
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