lsplsGlm: Classification using LS-PLS for Logistic Regression

Fit logistic regression models using LS-PLS approaches to analyse both clinical and genomic data. (C. Bazzoli and S. Lambert-Lacroix. (2017) Classification using LS-PLS with logistic regression based on both clinical and gene expression variables <https://hal.archives-ouvertes.fr/hal-01405101>).

Version: 1.0
Depends: R (≥ 3.0), methods, stats
Published: 2017-07-27
Author: Caroline Bazzoli, Sophie Lambert-Lacroix, Thomas Bouleau
Maintainer: Bazzoli Caroline <caroline.bazzoli at univ-grenoble-alpes.fr>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
CRAN checks: lsplsGlm results

Documentation:

Reference manual: lsplsGlm.pdf

Downloads:

Package source: lsplsGlm_1.0.tar.gz
Windows binaries: r-devel: lsplsGlm_1.0.zip, r-release: lsplsGlm_1.0.zip, r-oldrel: lsplsGlm_1.0.zip
macOS binaries: r-release (arm64): lsplsGlm_1.0.tgz, r-oldrel (arm64): lsplsGlm_1.0.tgz, r-release (x86_64): lsplsGlm_1.0.tgz, r-oldrel (x86_64): lsplsGlm_1.0.tgz

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