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: 0.2.5
Depends: R (≥ 2.4.0)
Imports: mvtnorm, boot, Formula, MASS, plsRglm, betareg, methods
Suggests: pls, plsdof
Published: 2019-02-01
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: http://www-irma.u-strasbg.fr/~fbertran/, https://github.com/fbertran/plsRbeta
NeedsCompilation: no
Classification/MSC: 62J12, 62J99
Citation: plsRbeta citation info
Materials: NEWS
In views: MissingData
CRAN checks: plsRbeta results

Downloads:

Reference manual: plsRbeta.pdf
Package source: plsRbeta_0.2.5.tar.gz
Windows binaries: r-prerelease: plsRbeta_0.2.5.zip, r-release: plsRbeta_0.2.5.zip, r-oldrel: plsRbeta_0.2.5.zip
macOS binaries: r-prerelease: plsRbeta_0.2.5.tgz, r-release: plsRbeta_0.2.5.tgz, r-oldrel: plsRbeta_0.2.5.tgz
Old sources: plsRbeta archive

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