Package: lars 1.3
lars: Least Angle Regression, Lasso and Forward Stagewise
Efficient procedures for fitting an entire lasso sequence with the cost of a single least squares fit. Least angle regression and infinitesimal forward stagewise regression are related to the lasso, as described in the paper below.
Authors:
lars_1.3.tar.gz
lars_1.3.zip(r-4.5)lars_1.3.zip(r-4.4)lars_1.3.zip(r-4.3)
lars_1.3.tgz(r-4.4-x86_64)lars_1.3.tgz(r-4.4-arm64)lars_1.3.tgz(r-4.3-x86_64)lars_1.3.tgz(r-4.3-arm64)
lars_1.3.tar.gz(r-4.5-noble)lars_1.3.tar.gz(r-4.4-noble)
lars_1.3.tgz(r-4.4-emscripten)lars_1.3.tgz(r-4.3-emscripten)
lars.pdf |lars.html✨
lars/json (API)
| # Install 'lars' in R: |
| install.packages('lars', repos = c('https://trevorhastie.r-universe.dev', 'https://cloud.r-project.org')) |
- diabetes - Blood and other measurements in diabetics
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 3 years agofrom:b2e7a9036b. Checks:9 OK. Indexed: yes.
| Target | Result | Latest binary |
|---|---|---|
| Doc / Vignettes | OK | Jan 04 2025 |
| R-4.5-win-x86_64 | OK | Jan 04 2025 |
| R-4.5-linux-x86_64 | OK | Jan 04 2025 |
| R-4.4-win-x86_64 | OK | Jan 04 2025 |
| R-4.4-mac-x86_64 | OK | Jan 04 2025 |
| R-4.4-mac-aarch64 | OK | Jan 04 2025 |
| R-4.3-win-x86_64 | OK | Jan 04 2025 |
| R-4.3-mac-x86_64 | OK | Jan 04 2025 |
| R-4.3-mac-aarch64 | OK | Jan 04 2025 |
Exports:backsolvetbetabreakercoef.larscv.foldscv.larsdelcoldowndateRerror.barslarsnnls.larsplot.larsplotCVLarspredict.larsprint.larssummary.larsupdateR
Dependencies:
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Computes K-fold cross-validated error curve for lars | cv.lars |
| Blood and other measurements in diabetics | diabetes |
| Fits Least Angle Regression, Lasso and Infinitesimal Forward Stagewise regression models | lars |
| Plot method for lars objects | plot.lars |
| Make predictions or extract coefficients from a fitted lars model | coef.lars predict.lars |
| Summary method for lars objects | summary.lars |
