rclsp
A Modular Two-Step Convex Optimization Estimator for Ill-Posed Problems
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.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.5.0 |
rolling linux/jammy R-4.5 | rclsp_0.5.0.tar.gz |
69.3 KiB |
0.5.0 |
rolling linux/noble R-4.5 | rclsp_0.5.0.tar.gz |
69.3 KiB |
0.5.0 |
rolling source/ R- | rclsp_0.5.0.tar.gz |
17.2 KiB |
0.5.0 |
latest linux/jammy R-4.5 | rclsp_0.5.0.tar.gz |
69.3 KiB |
0.5.0 |
latest linux/noble R-4.5 | rclsp_0.5.0.tar.gz |
69.3 KiB |
0.5.0 |
latest source/ R- | rclsp_0.5.0.tar.gz |
17.2 KiB |
0.5.0 |
2026-04-26 source/ R- | rclsp_0.5.0.tar.gz |
17.2 KiB |
0.5.0 |
2026-04-23 source/ R- | rclsp_0.5.0.tar.gz |
17.2 KiB |
0.5.0 |
2026-04-09 windows/windows R-4.5 | rclsp_0.5.0.zip |
71.8 KiB |