Data-Driven Sparse PLS Robust to Missing Samples for Mono and Multi-Block Data Sets

Allows to build Multi-Data-Driven Sparse PLS models. Multi-blocks with high-dimensional settings are particularly sensible to this.

A sparse PLS formulation for mono and multi-block data sets with missing samples


Reference manual

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1.0.61 by Hadrien Lorenzo, 6 months ago

Browse source code at

Authors: Hadrien Lorenzo [aut, cre] , Jerome Saracco [aut] , Rodolphe Thiebaut [aut]

Documentation:   PDF Manual  

Task views: Missing Data

MIT + file LICENSE license

Imports RColorBrewer, MASS, graphics, stats, Rdpack, doParallel, foreach, parallel

Suggests knitr, rmarkdown

See at CRAN