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carsAlgo  

Competitive Adaptive Reweighted Sampling (CARS) Algorithm
View on CRAN: Click here


Download and install carsAlgo package within the R console
Install from CRAN:
install.packages("carsAlgo")

Install from Github:
library("remotes")
install_github("cran/carsAlgo")

Install by package version:
library("remotes")
install_version("carsAlgo", "0.5.0")



Attach the package and use:
library("carsAlgo")
Maintained by
Md. Ashraful Haque
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-04-16
Latest Update: 2026-04-16
Description:
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.
How to cite:
Md. Ashraful Haque (2026). carsAlgo: Competitive Adaptive Reweighted Sampling (CARS) Algorithm. R package version 0.5.0, https://cran.r-project.org/web/packages/carsAlgo. Accessed 04 Oct. 2026.
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