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: | 1.6.0 |
| Depends: | R (≥ 2.10) |
| Imports: | mvtnorm, boot, bipartite, car, MASS |
| Suggests: | chemometrics, plsdof, plsdepot, plspm, plsRcox, R.rsp, testthat (≥ 3.0.0) |
| Enhances: | pls |
| Published: | 2025-09-12 |
| DOI: | 10.32614/CRAN.package.plsRglm |
| Author: | Frederic Bertrand 
[cre, aut],
Myriam Maumy-Bertrand
[aut] |
| Maintainer: | Frederic Bertrand <frederic.bertrand at lecnam.net> |
| 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.html , plsRglm.pdf |
| Vignettes: |
plsRglm: Manual (source) plsRglm: Algorithmic insights and applications (source) |
Downloads:
| Package source: | plsRglm_1.6.0.tar.gz |
| Windows binaries: | r-devel: plsRglm_1.6.0.zip, r-release: plsRglm_1.6.0.zip, r-oldrel: plsRglm_1.6.0.zip |
| macOS binaries: | r-release (arm64): plsRglm_1.6.0.tgz, r-oldrel (arm64): plsRglm_1.6.0.tgz, r-release (x86_64): plsRglm_1.6.0.tgz, r-oldrel (x86_64): plsRglm_1.6.0.tgz |
| Old sources: | plsRglm archive |
Reverse dependencies:
| Reverse imports: | bootPLS, plsRbeta, plsRcox |
| Reverse suggests: | bigPLSR |
Linking:
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