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:Congrui Yi [aut, cre]

hqreg_1.4-1.tar.gz
hqreg_1.4-1.zip(r-4.5)hqreg_1.4-1.zip(r-4.4)hqreg_1.4-1.zip(r-4.3)
hqreg_1.4-1.tgz(r-4.5-x86_64)hqreg_1.4-1.tgz(r-4.5-arm64)hqreg_1.4-1.tgz(r-4.4-x86_64)hqreg_1.4-1.tgz(r-4.4-arm64)hqreg_1.4-1.tgz(r-4.3-x86_64)hqreg_1.4-1.tgz(r-4.3-arm64)
hqreg_1.4-1.tar.gz(r-4.5-noble)hqreg_1.4-1.tar.gz(r-4.4-noble)
hqreg_1.4-1.tgz(r-4.4-emscripten)hqreg_1.4-1.tgz(r-4.3-emscripten)
hqreg.pdf |hqreg.html
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

On CRAN:

Conda:

elastic-nethigh-dimensionalhuber-loss-regressionlassomachine-learning-algorithmsquantile-regressionregularization-paths

6.31 score 10 stars 4 packages 57 scripts 712 downloads 2 mentions 3 exports 0 dependencies

Last updated 5 months agofrom:840a555e81. Checks:1 OK, 11 NOTE. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 09 2025
R-4.5-win-x86_64NOTEMar 09 2025
R-4.5-mac-x86_64NOTEMar 09 2025
R-4.5-mac-aarch64NOTEMar 09 2025
R-4.5-linux-x86_64NOTEMar 09 2025
R-4.4-win-x86_64NOTEMar 09 2025
R-4.4-mac-x86_64NOTEMar 09 2025
R-4.4-mac-aarch64NOTEMar 09 2025
R-4.4-linux-x86_64NOTEMar 09 2025
R-4.3-win-x86_64NOTEMar 09 2025
R-4.3-mac-x86_64NOTEMar 09 2025
R-4.3-mac-aarch64NOTEMar 09 2025

Exports:cv.hqreghqreghqreg_raw

Dependencies: