carsAlgo: Competitive Adaptive Reweighted Sampling (CARS) Algorithm
Implements Competitive Adaptive Reweighted Sampling (CARS)
algorithm for variable selection from high-dimensional dataset using Partial
Least Squares (PLS) regression models. CARS algorithm iteratively applies the
Monte Carlo sub-sampling and exponential variable elimination techniques to
identify/select the most informative variables/features subjected to minimal
cross-validated RMSE score. The implementation of CARS algorithm is inspired
from the work of Li et al. (2009) <doi:10.1016/j.aca.2009.06.046>.
This algorithm is widely applied in near-infrared (NIR), mid-infrared (MIR),
hyperspectral chemometrics areas, etc.
| Version: |
0.5.0 |
| Depends: |
R (≥ 4.1.0) |
| Imports: |
ggplot2, pls, rlang, stats, utils |
| Published: |
2026-04-16 |
| DOI: |
10.32614/CRAN.package.carsAlgo (may not be active yet) |
| Author: |
Md. Ashraful Haque [aut, cre],
Avijit Ghosh [aut],
Sayantani Karmakar [aut],
Harsh Sachan [aut],
Shalini Kumari [aut] |
| Maintainer: |
Md. Ashraful Haque <ashrafulhaque664 at gmail.com> |
| BugReports: |
https://github.com/mah-iasri/carsAlgo/issues |
| License: |
MIT + file LICENSE |
| URL: |
https://github.com/mah-iasri/carsAlgo |
| NeedsCompilation: |
no |
| Materials: |
README, NEWS |
| CRAN checks: |
carsAlgo results |
Documentation:
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