R package ddsPLS: 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.

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References in zbMATH (referenced in 1 article , 1 standard article )

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  1. Hadrien Lorenzo, Jérôme Saracco, Rodolphe Thiébaut: Supervised Learning for Multi-Block Incomplete Data (2019) arXiv