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:

Reference manual:

carsAlgo.html , carsAlgo.pdf

Downloads:

Package source:	carsAlgo_0.5.0.tar.gz
Windows binaries:	r-devel: not available, r-release: not available, r-oldrel: not available
macOS binaries:	r-release (arm64): not available, r-oldrel (arm64): not available, r-release (x86_64): not available, r-oldrel (x86_64): not available

Linking:

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