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rclsp  

A Modular Two-Step Convex Optimization Estimator for Ill-Posed Problems
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("rclsp", "0.2.0")



Attach the package and use:
library("rclsp")
Maintained by
Ilya Bolotov
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2025-11-17
Latest Update: 2025-11-17
Description:
Convex Least Squares Programming (CLSP) is a two-step estimator for solving underdetermined, ill-posed, or structurally constrained least-squares problems. It combines pseudoinverse-based estimation with convex-programming correction methods inspired by Lasso, Ridge, and Elastic Net to ensure numerical stability, constraint enforcement, and interpretability. The package also provides numerical stability analysis and CLSP-specific diagnostics, including partial R^2, normalized RMSE (NRMSE), Monte Carlo t-tests for mean NRMSE, and condition-number-based confidence bands.
How to cite:
Ilya Bolotov (2025). rclsp: A Modular Two-Step Convex Optimization Estimator for Ill-Posed Problems. R package version 0.2.0, https://cran.r-project.org/web/packages/rclsp. Accessed 11 Mar. 2026.
Previous versions and publish date:
0.1.0 (2025-11-17 22:10), 0.2.0 (2025-11-26 14:40), 0.3.0 (2026-01-30 17:30), 0.4.0 (2026-02-19 16:10)
Other packages that cited rclsp R package
View rclsp citation profile
Other R packages that rclsp depends, imports, suggests or enhances
Complete documentation for rclsp
Functions, R codes and Examples using the rclsp R package
Full rclsp package functions and examples
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