Package: hqreg 1.4-1
hqreg: Regularization Paths for Lasso or Elastic-Net Penalized Huber Loss Regression and Quantile Regression
Offers efficient algorithms for fitting regularization paths for lasso or elastic-net penalized regression models with Huber loss, quantile loss or squared loss. Reference: Congrui Yi and Jian Huang (2017) <doi:10.1080/10618600.2016.1256816>.
Authors:
hqreg_1.4-1.tar.gz
hqreg_1.4-1.zip(r-4.7)hqreg_1.4-1.zip(r-4.6)hqreg_1.4-1.zip(r-4.5)
hqreg_1.4-1.tgz(r-4.6-x86_64)hqreg_1.4-1.tgz(r-4.6-arm64)hqreg_1.4-1.tgz(r-4.5-x86_64)hqreg_1.4-1.tgz(r-4.5-arm64)
hqreg_1.4-1.tar.gz(r-4.7-arm64)hqreg_1.4-1.tar.gz(r-4.7-x86_64)hqreg_1.4-1.tar.gz(r-4.6-arm64)hqreg_1.4-1.tar.gz(r-4.6-x86_64)
hqreg_1.4-1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
hqreg/json (API)
NEWS
| # Install 'hqreg' in R: |
| install.packages('hqreg', repos = c('https://cy-dev.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/cy-dev/hqreg/issues
elastic-nethigh-dimensionalhuber-loss-regressionlassomachine-learning-algorithmsquantile-regressionregularization-paths
Last updated from:840a555e81. Checks:11 NOTE, 2 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-arm64 | NOTE | 97 | ||
| linux-devel-x86_64 | NOTE | 104 | ||
| source / vignettes | OK | 118 | ||
| linux-release-arm64 | NOTE | 96 | ||
| linux-release-x86_64 | NOTE | 105 | ||
| macos-release-arm64 | NOTE | 95 | ||
| macos-release-x86_64 | NOTE | 263 | ||
| macos-oldrel-arm64 | NOTE | 95 | ||
| macos-oldrel-x86_64 | NOTE | 228 | ||
| windows-devel | NOTE | 71 | ||
| windows-release | NOTE | 77 | ||
| windows-oldrel | NOTE | 86 | ||
| wasm-release | OK | 98 |
Exports:cv.hqreghqreghqreg_raw
Dependencies:
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Regularization Paths for Lasso or Elastic-net Penalized Huber Loss Regression and Quantile Regression | hqreg-package |
| Cross-validation for hqreg | cv.hqreg |
| Fit a robust regression model with Huber or quantile loss penalized by lasso or elasti-net | hqreg |
| Fit a robust regression model on raw data with Huber or quantile loss penalized by lasso or elasti-net | hqreg_raw |
| Plot the cross-validation curve for a "cv.hqreg" object | plot.cv.hqreg |
| Plot coefficients from a "hqreg" object | plot.hqreg |
| Model predictions based on "cv.hqreg" object. | coef.cv.hqreg predict.cv.hqreg |
| Model predictions based on "hqreg" object. | coef.hqreg predict.hqreg |
