Allows to build Multi-Data-Driven Sparse Partial Least Squares models. Multi-blocks with high-dimensional settings are particularly sensible to this. It comes with visualization functions and uses 'Rcpp' functions for fast computations and 'doParallel' to parallelize cross-validation. This is based on H Lorenzo, J Saracco, R Thiebaut (2019) <arXiv:1901.04380>. Many applications have been successfully realized. See <https://hadrienlorenzo.netlify.com/> for more information, documentation and examples.
Version: | 1.1.4 |
Depends: | R (≥ 2.10) |
Imports: | RColorBrewer, MASS, graphics, stats, Rdpack, doParallel, foreach, parallel, corrplot, Rcpp (≥ 0.12.18) |
LinkingTo: | Rcpp |
Suggests: | knitr, rmarkdown, htmltools |
Published: | 2020-03-02 |
Author: | Hadrien Lorenzo [aut, cre], Misbah Razzaq [ctb], Jerome Saracco [aut], Rodolphe Thiebaut [aut] |
Maintainer: | Hadrien Lorenzo <hadrien.lorenzo.2015 at gmail.com> |
License: | MIT + file LICENSE |
URL: | https://hadrienlorenzo.netlify.com/ |
NeedsCompilation: | yes |
Citation: | ddsPLS citation info |
Materials: | README |
In views: | MissingData |
CRAN checks: | ddsPLS results |
Reference manual: | ddsPLS.pdf |
Vignettes: |
ddsPLS : A Package to Deal with Multi-Block Supervised Problems with Missing Samples in High Dimension |
Package source: | ddsPLS_1.1.4.tar.gz |
Windows binaries: | r-devel: ddsPLS_1.1.4.zip, r-release: ddsPLS_1.1.4.zip, r-oldrel: ddsPLS_1.1.4.zip |
macOS binaries: | r-release: ddsPLS_1.1.4.tgz, r-oldrel: ddsPLS_1.1.4.tgz |
Old sources: | ddsPLS archive |
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