plsRbeta: Partial Least Squares Regression for Beta Regression Models

Provides Partial least squares Regression for (weighted) beta regression models (Bertrand 2013, <http://journal-sfds.fr/article/view/215>) and k-fold cross-validation of such models using various criteria. It allows for missing data in the explanatory variables. Bootstrap confidence intervals constructions are also available.

Version: 0.2.6
Depends: R (≥ 2.4.0)
Imports: mvtnorm, boot, Formula, MASS, plsRglm, betareg, methods
Suggests: pls, plsdof
Published: 2021-03-18
Author: Frederic Bertrand ORCID iD [cre, aut], Myriam Maumy-Bertrand ORCID iD [aut]
Maintainer: Frederic Bertrand <frederic.bertrand at math.unistra.fr>
BugReports: https://github.com/fbertran/plsRbeta/issues/
License: GPL-3
URL: https://fbertran.github.io/plsRbeta/, https://github.com/fbertran/plsRbeta/
NeedsCompilation: no
Classification/MSC: 62J12, 62J99
Citation: plsRbeta citation info
Materials: README
In views: MissingData
CRAN checks: plsRbeta results

Documentation:

Reference manual: plsRbeta.pdf

Downloads:

Package source: plsRbeta_0.2.6.tar.gz
Windows binaries: r-devel: plsRbeta_0.2.6.zip, r-release: plsRbeta_0.2.6.zip, r-oldrel: plsRbeta_0.2.6.zip
macOS binaries: r-release (arm64): plsRbeta_0.2.6.tgz, r-oldrel (arm64): plsRbeta_0.2.6.tgz, r-release (x86_64): plsRbeta_0.2.6.tgz, r-oldrel (x86_64): plsRbeta_0.2.6.tgz
Old sources: plsRbeta archive

Linking:

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