SCGLR: Supervised Component Generalized Linear Regression

An extension of the Fisher Scoring Algorithm to combine PLS regression with GLM estimation in the multivariate context. Covariates can also be grouped in themes.

Version: 3.0
Depends: R (≥ 3.0.0)
Imports: Matrix, Formula, expm, graphics, ggplot2, grid, pROC, ade4
Suggests: parallel, gridExtra
Published: 2018-09-28
Author: Guillaume Cornu ORCID iD [aut, cre], Frederic Mortier [aut], Catherine Trottier [aut], Xavier Bry [aut], Sylvie Gourlet-Fleury ORCID iD [dtc] (http://www.coforchange.eu/), Claude Garcia ORCID iD [dtc] (http://www.cofortips.org/)
Maintainer: Guillaume Cornu <gcornu at cirad.fr>
BugReports: https://github.com/SCnext/SCGLR/issues
License: CeCILL-2 | GPL-2
URL: https://scnext.github.io/SCGLR, https://github.com/SCnext/SCGLR, https://cran.r-project.org/package=SCGLR
NeedsCompilation: no
Materials: README NEWS
CRAN checks: SCGLR results

Documentation:

Reference manual: SCGLR.pdf

Downloads:

Package source: SCGLR_3.0.tar.gz
Windows binaries: r-devel: SCGLR_3.0.zip, r-release: SCGLR_3.0.zip, r-oldrel: SCGLR_3.0.zip
macOS binaries: r-release (arm64): SCGLR_3.0.tgz, r-release (x86_64): SCGLR_3.0.tgz, r-oldrel: SCGLR_3.0.tgz
Old sources: SCGLR archive

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