Sparse and Non-Sparse Partial Robust M Regression and Classification

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.


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install.packages("sprm")

1.2.2 by Irene Hoffmann, 2 years ago


Browse source code at https://github.com/cran/sprm


Authors: Sven Serneels (BASF Corp) and Irene Hoffmann


Documentation:   PDF Manual  


GPL (>= 3) license


Imports cvTools, graphics, grDevices, grid, pcaPP, reshape2, robustbase, stats

Depends on ggplot2


See at CRAN