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:Ilya Bolotov [aut, cre]

rclsp_2.0.1.tar.gz
rclsp_2.0.1.zip(r-4.7-any)rclsp_2.0.1.zip(r-4.6-any)rclsp_2.0.1.zip(r-4.5-any)
rclsp_2.0.1.tgz(r-4.6-any)rclsp_2.0.1.tgz(r-4.5-any)
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✨
DESCRIPTION |NEWS
card.svg |card.png
rclsp/json (API)

# Install 'rclsp' in R:
install.packages('rclsp', repos = c('https://econcz.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/econcz/rclsp/issues

On CRAN:

Conda:

convex-optimizationestimatorsgeneralized-inverseleast-squaresregularization

4.56 score 1 stars 3 packages 326 downloads 4 exports 15 dependencies

Last updated from:f7813e5e20. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK126
source / vignettesOK178
linux-releaseOK167
macos-releaseOK97
macos-oldrelOK89
windows-develOK69
windows-releaseOK66
windows-oldrelOK66
wasm-releaseOK110

Exports:canonizeclspcorrttest

Dependencies:backportscheckmateclarabelcliCVXRgmphighslatticeMatrixosqpRcppRcppEigenS7scsslam