Package: rclsp 2.0.1
Ilya Bolotov
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.
Authors:
rclsp_2.0.1.tar.gz
rclsp_2.0.1.tar.gz(r-4.7-any)rclsp_2.0.1.tar.gz(r-4.6-any)
rclsp_2.0.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
rclsp/json (API)
NEWS
| # Install 'rclsp' in R: |
| install.packages('rclsp', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/econcz/rclsp/issues
Last updated from:b8b4174063. Checks:4 OK. Indexed: no.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 122 | ||
| source / vignettes | OK | 199 | ||
| linux-release-x86_64 | OK | 119 | ||
| wasm-release | OK | 125 |
Dependencies:backportscheckmateclarabelcliCVXRgmphighslatticeMatrixosqpRcppRcppEigenS7scsslam
