rclsp: A Modular Two-Step Convex Optimization Estimator for Ill-PosedProblems
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.
| Version: | 0.2.0 |
| Depends: | R (≥ 4.2) |
| Imports: | Matrix, stats, methods,CVXR,MASS |
| Suggests: | testthat (≥ 3.0.0) |
| Published: | 2025-11-26 |
| DOI: | 10.32614/CRAN.package.rclsp |
| Author: | Ilya Bolotov [aut, cre] |
| Maintainer: | Ilya Bolotov <ilya.bolotov at vse.cz> |
| BugReports: | https://github.com/econcz/rclsp/issues |
| License: | MIT + fileLICENSE |
| URL: | https://github.com/econcz/rclsp |
| NeedsCompilation: | no |
| Language: | en-US |
| Materials: | README |
| CRAN checks: | rclsp results |
Documentation:
| Reference manual: | rclsp.html ,rclsp.pdf |
Downloads:
| Package source: | rclsp_0.2.0.tar.gz |
| Windows binaries: | r-devel:rclsp_0.2.0.zip, r-release:rclsp_0.2.0.zip, r-oldrel:rclsp_0.2.0.zip |
| macOS binaries: | r-release (arm64):rclsp_0.2.0.tgz, r-oldrel (arm64):rclsp_0.2.0.tgz, r-release (x86_64):rclsp_0.2.0.tgz, r-oldrel (x86_64):rclsp_0.2.0.tgz |
| Old sources: | rclsp archive |
Reverse dependencies:
| Reverse imports: | rlppinv,rtmpinv |
Linking:
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