ddsPLS: Multi-Data-Driven Sparse PLS Robust to Missing Samples

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

Version: 1.0.0
Depends: R (≥ 2.10)
Imports: RColorBrewer, MASS, graphics, stats, utils, Rdpack, doParallel, foreach, parallel, iterators
Suggests: knitr, rmarkdown
Published: 2018-09-19
Author: Hadrien Lorenzo [aut, cre]
Maintainer: Hadrien Lorenzo <hadrien.lorenzo.2015 at>
License: MIT + file LICENSE
NeedsCompilation: no
Materials: README
CRAN checks: ddsPLS results


Reference manual: ddsPLS.pdf
Vignettes: Vignette Title
Package source: ddsPLS_1.0.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel: not available
OS X binaries: r-release: not available, r-oldrel: ddsPLS_1.0.0.tgz


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