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 <arXiv:1810.01005>. It allows for missing data in the explanatory variables. Bootstrap confidence intervals constructions are also available.
Version: |
1.5.0 |
Depends: |
R (≥ 2.10) |
Imports: |
mvtnorm, boot, bipartite, car, MASS |
Suggests: |
plsdof, R.rsp, chemometrics, plsdepot |
Enhances: |
pls |
Published: |
2022-05-02 |
Author: |
Frederic Bertrand
[cre, aut],
Myriam Maumy-Bertrand
[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 |
Documentation:
Downloads:
Reverse dependencies:
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