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
DOI:	10.32614/CRAN.package.plsRglm
Author:	Frederic Bertrand [cre, aut], Myriam Maumy-Bertrand [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:

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