sprm: 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.

AuthorSven Serneels (BASF Corp) and Irene Hoffmann
Date of publication2016-02-22 14:33:44
MaintainerIrene Hoffmann <irene.hoffmann@tuwien.ac.at>
LicenseGPL (>= 3)
Version1.2.2

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