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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: |
0.3.0 |
| Depends: |
R (≥ 3.5.0) |
| Imports: |
mvtnorm, boot, Formula, MASS, plsRglm, betareg, methods |
| Suggests: |
bipartite, knitr, markdown, plotrix, pls, plsdof, prettydoc, rmarkdown |
| Published: |
2023-03-15 |
| Author: |
Frederic Bertrand 
[cre, aut],
Myriam Maumy-Bertrand
[aut] |
| Maintainer: |
Frederic Bertrand <frederic.bertrand at utt.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:
Downloads:
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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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