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 |
| 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 |
| Reference manual: | carsAlgo.html , carsAlgo.pdf |
| Package source: | carsAlgo_0.5.0.tar.gz |
| Windows binaries: | r-devel: carsAlgo_0.5.0.zip, r-release: carsAlgo_0.5.0.zip, r-oldrel: carsAlgo_0.5.0.zip |
| macOS binaries: | r-release (arm64): carsAlgo_0.5.0.tgz, r-oldrel (arm64): carsAlgo_0.5.0.tgz, r-release (x86_64): carsAlgo_0.5.0.tgz, r-oldrel (x86_64): carsAlgo_0.5.0.tgz |
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