Package: l0ara 0.1.7
l0ara: Sparse Generalized Linear Model with L0 Approximation for Feature Selection
Fits sparse generalized linear models using an adaptive ridge approximation to an L0 penalty. Supported model families include Gaussian, logistic, Poisson, gamma, and inverse Gaussian regression. The package also provides cross-validation for selecting the penalty parameter.
Authors:
l0ara_0.1.7.tar.gz
l0ara_0.1.7.zip(r-4.7)l0ara_0.1.7.zip(r-4.6)l0ara_0.1.7.zip(r-4.5)
l0ara_0.1.7.tgz(r-4.6-x86_64)l0ara_0.1.7.tgz(r-4.6-arm64)l0ara_0.1.7.tgz(r-4.5-x86_64)l0ara_0.1.7.tgz(r-4.5-arm64)
l0ara_0.1.7.tar.gz(r-4.7-arm64)l0ara_0.1.7.tar.gz(r-4.7-x86_64)l0ara_0.1.7.tar.gz(r-4.6-arm64)l0ara_0.1.7.tar.gz(r-4.6-x86_64)
l0ara_0.1.7.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
l0ara/json (API)
NEWS
| # Install 'l0ara' in R: |
| install.packages('l0ara', repos = c('https://wgost.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated from:1cb2c0bf3d. Checks:13 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-arm64 | OK | 136 | ||
| linux-devel-x86_64 | OK | 110 | ||
| source / vignettes | OK | 148 | ||
| linux-release-arm64 | OK | 112 | ||
| linux-release-x86_64 | OK | 107 | ||
| macos-release-arm64 | OK | 87 | ||
| macos-release-x86_64 | OK | 174 | ||
| macos-oldrel-arm64 | OK | 98 | ||
| macos-oldrel-x86_64 | OK | 246 | ||
| windows-devel | OK | 89 | ||
| windows-release | OK | 101 | ||
| windows-oldrel | OK | 98 | ||
| wasm-release | OK | 102 |
Dependencies:RcppRcppArmadillo
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Extract coefficients from a '"cv.l0ara"' object | coef.cv.l0ara |
| Extract coefficients from a '"l0ara"' object | coef.l0ara |
| Cross-validation for l0ara | cv.l0ara |
| Fit a generalized linear model with an L0 penalty | l0ara |
| Plot a '"cv.l0ara"' object | plot.cv.l0ara |
| Plot a '"l0ara"' object | plot.l0ara |
| Make predictions from a '"l0ara"' object | predict.l0ara |
| Print a '"cv.l0ara"' object | print.cv.l0ara |
| Print a '"l0ara"' object | print.l0ara |
