A sparse Partial Least Squares implementation which uses soft-thresholdestimation of the covariance matrices and therein introducessparsity. Number of components and regularization coefficients are automatically set.
| Version: | 1.2.1 |
| Depends: | foreach, R (≥ 2.10) |
| Imports: | Rcpp (≥ 1.0.5),doParallel,shiny,RColorBrewer |
| LinkingTo: | Rcpp,RcppEigen |
| Suggests: | knitr,rmarkdown,MASS |
| Published: | 2024-01-30 |
| DOI: | 10.32614/CRAN.package.ddsPLS |
| Author: | Hadrien Lorenzo |
| Maintainer: | Hadrien Lorenzo <hadrien.lorenzo.2015 at gmail.com> |
| License: | MIT + fileLICENSE |
| NeedsCompilation: | yes |
| Citation: | ddsPLS citation info |
| Materials: | README |
| CRAN checks: | ddsPLS results |
| Reference manual: | ddsPLS.html ,ddsPLS.pdf |
| Vignettes: | Data-Driven Sparse PLS (ddsPLS) (source,R code) |
| Package source: | ddsPLS_1.2.1.tar.gz |
| Windows binaries: | r-devel:ddsPLS_1.2.1.zip, r-release:ddsPLS_1.2.1.zip, r-oldrel:ddsPLS_1.2.1.zip |
| macOS binaries: | r-release (arm64):ddsPLS_1.2.1.tgz, r-oldrel (arm64):ddsPLS_1.2.1.tgz, r-release (x86_64):ddsPLS_1.2.1.tgz, r-oldrel (x86_64):ddsPLS_1.2.1.tgz |
| Old sources: | ddsPLS archive |
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