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plsRglm: Partial Least Squares Regression for Generalized Linear Models

Provides (weighted) Partial least squares Regression for generalized linear models and repeated k-fold cross-validation of such models using various criteria <doi:10.48550/arXiv.1810.01005>. It allows for missing data in the explanatory variables. Bootstrap confidence intervals constructions are also available.

Version: 1.5.1
Depends: R (≥ 2.10)
Imports: mvtnorm, boot, bipartite, car, MASS
Suggests: plsdof, R.rsp, chemometrics, plsdepot
Enhances: pls
Published: 2023-03-14
Author: Frederic Bertrand ORCID iD [cre, aut], Myriam Maumy-Bertrand ORCID iD [aut]
Maintainer: Frederic Bertrand <frederic.bertrand at utt.fr>
BugReports: https://github.com/fbertran/plsRglm/issues/
License: GPL-3
URL: https://fbertran.github.io/plsRglm/, https://github.com/fbertran/plsRglm/
NeedsCompilation: no
Classification/MSC: 62J12, 62J99
Citation: plsRglm citation info
Materials: NEWS
In views: MissingData
CRAN checks: plsRglm results

Documentation:

Reference manual: plsRglm.pdf
Vignettes: plsRglm: Manual
plsRglm: Algorithmic insights and applications

Downloads:

Package source: plsRglm_1.5.1.tar.gz
Windows binaries: r-devel: plsRglm_1.5.1.zip, r-release: plsRglm_1.5.1.zip, r-oldrel: plsRglm_1.5.1.zip
macOS binaries: r-release (arm64): plsRglm_1.5.1.tgz, r-oldrel (arm64): plsRglm_1.5.1.tgz, r-release (x86_64): plsRglm_1.5.1.tgz, r-oldrel (x86_64): plsRglm_1.5.1.tgz
Old sources: plsRglm archive

Reverse dependencies:

Reverse imports: bootPLS, plsRbeta, plsRcox

Linking:

Please use the canonical form https://CRAN.R-project.org/package=plsRglm to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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