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PRIMAL  

Parametric Simplex Method for Sparse Learning
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("PRIMAL", "1.0.3")



Attach the package and use:
library("PRIMAL")
Maintained by
Zichong Li
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2019-10-02
Latest Update: 2020-01-22
Description:
Implements a unified framework of parametric simplex method for a variety of sparse learning problems (e.g., Dantzig selector (for linear regression), sparse quantile regression, sparse support vector machines, and compressive sensing) combined with efficient hyper-parameter selection strategies. The core algorithm is implemented in C++ with Eigen3 support for portable high performance linear algebra. For more details about parametric simplex method, see Haotian Pang (2017) .
How to cite:
Zichong Li (2019). PRIMAL: Parametric Simplex Method for Sparse Learning. R package version 1.0.3, https://cran.r-project.org/web/packages/PRIMAL. Accessed 05 Oct. 2026.
Previous versions and publish date:
(2026-07-09 08:16), 1.0.0 (2019-10-02 12:00), 1.0.1 (2020-01-12 15:40), 1.0.2 (2020-01-22 12:10)
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Complete documentation for PRIMAL
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