Package: rclsp 2.0.0

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_2.0.0.tar.gz
rclsp_2.0.0.zip(r-4.7)rclsp_2.0.0.zip(r-4.6)rclsp_2.0.0.zip(r-4.5)
rclsp_2.0.0.tgz(r-4.6-any)rclsp_2.0.0.tgz(r-4.5-any)
rclsp_2.0.0.tar.gz(r-4.7-any)rclsp_2.0.0.tar.gz(r-4.6-any)
rclsp_2.0.0.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://econcz.r-universe.dev', 'https://cloud.r-project.org'))

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

On CRAN:

Conda:

convex-optimizationestimatorsgeneralized-inverseleast-squaresregularization

4.50 score 1 stars 3 packages 577 downloads 4 exports 15 dependencies

Last updated from:eeee531380. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK127
source / vignettesOK184
linux-release-x86_64OK128
macos-release-arm64OK87
macos-oldrel-arm64OK80
windows-develOK111
windows-releaseOK73
windows-oldrelOK78
wasm-releaseOK126

Exports:canonizeclspcorrttest

Dependencies:backportscheckmateclarabelcliCVXRgmphighslatticeMatrixosqpRcppRcppEigenS7scsslam