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-4.7-x86_64)hqreg_1.4-1.zip(r-4.7-arm64)hqreg_1.4-1.zip(r-4.6-x86_64)hqreg_1.4-1.zip(r-4.6-arm64)hqreg_1.4-1.zip(r-4.5-x86_64)
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✨
DESCRIPTION |NEWS
card.svg |card.png
hqreg/json (API)

# 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

5.89 score 10 stars 4 packages 64 scripts 722 downloads 2 mentions 3 exports 0 dependencies

Last updated from:840a555e81. Checks:13 NOTE, 2 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64NOTE75
linux-devel-x86_64NOTE90
source / vignettesOK187
linux-release-arm64NOTE75
linux-release-x86_64NOTE86
macos-release-arm64NOTE158
macos-release-x86_64NOTE250
macos-oldrel-arm64NOTE195
macos-oldrel-x86_64NOTE193
windows-devel-arm64NOTE311
windows-devel-x86_64NOTE109
windows-release-arm64NOTE309
windows-release-x86_64NOTE63
windows-oldrel-x86_64NOTE63
wasm-releaseOK66

Exports:cv.hqreghqreghqreg_raw

Dependencies: