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
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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'))

Peer review:

Bug tracker:https://github.com/cy-dev/hqreg/issues

On CRAN:

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

6.30 score 10 stars 4 packages 56 scripts 876 downloads 2 mentions 3 exports 0 dependencies

Last updated 14 days agofrom:840a555e81. Checks:OK: 1 NOTE: 8. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 09 2024
R-4.5-win-x86_64NOTENov 09 2024
R-4.5-linux-x86_64NOTENov 09 2024
R-4.4-win-x86_64NOTENov 09 2024
R-4.4-mac-x86_64NOTENov 09 2024
R-4.4-mac-aarch64NOTENov 09 2024
R-4.3-win-x86_64NOTENov 09 2024
R-4.3-mac-x86_64NOTENov 09 2024
R-4.3-mac-aarch64NOTENov 09 2024

Exports:cv.hqreghqreghqreg_raw

Dependencies: