ppls: Penalized Partial Least Squares
Linear and nonlinear regression
methods based on Partial Least Squares and Penalization
Techniques. Model parameters are selected via cross-validation,
and confidence intervals ans tests for the regression
coefficients can be conducted via jackknifing.
The method is described and applied to simulated and experimental
data in Kraemer et al. (2008) <doi:10.1016/j.chemolab.2008.06.009>.
| Version: |
2.0.0 |
| Depends: |
R (≥ 3.5.0) |
| Imports: |
splines, MASS |
| Published: |
2025-07-22 |
| DOI: |
10.32614/CRAN.package.ppls |
| Author: |
Nicole Kraemer [aut],
Anne-Laure Boulesteix [aut],
Vincent Guillemot [cre, aut] |
| Maintainer: |
Vincent Guillemot <vincent.guillemot at pasteur.fr> |
| License: |
GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: |
no |
| Citation: |
ppls citation info |
| Materials: |
README, NEWS |
| CRAN checks: |
ppls results |
Documentation:
Downloads:
Linking:
Please use the canonical form
https://CRAN.R-project.org/package=ppls
to link to this page.