doi:10.48550/arXiv.1810.01005>. It allows for missing data in the explanatory variables. Bootstrap confidence intervals constructions are also available.">

plsRglm: Partial Least Squares Regression for Generalized Linear Models (original) (raw)

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: 1.5.1
Depends: R (≥ 2.10)
Imports: mvtnorm, boot, bipartite, car, MASS
Suggests: plsdof, R.rsp, chemometrics, plsdepot
Enhances: pls
Published: 2023-03-14
DOI: 10.32614/CRAN.package.plsRglm
Author: Frederic Bertrand ORCID iD [cre, aut], Myriam Maumy-BertrandORCID iD [aut]
Maintainer: Frederic Bertrand <frederic.bertrand at utt.fr>
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

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