plsRbeta: Partial Least Squares Regression for Beta Regression Models

Provides Partial least squares Regression for (weighted) beta regression models (Bertrand 2013, <>) 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>
License: GPL-3
NeedsCompilation: no
Classification/MSC: 62J12, 62J99
Citation: plsRbeta citation info
Materials: README
In views: MissingData
CRAN checks: plsRbeta results


Reference manual: plsRbeta.pdf


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


Please use the canonical form to link to this page.