hrqglas

cranv1.1.2

Group Variable Selection for Quantile and Robust Mean Regression. A program that conducts group variable selection for quantile and robust mean regression (Sherwood and Li, 2022). The group lasso penalty (Yuan and Lin, 2006) is used for group-wise variable selection. Both of the quantile and mean regression models are based on the Huber loss. Specifically, with th

License GPL (>= 2)0 versions1 maintainers4 deps144 weekly dl
shaobo-li/hrqglas
35
/ 100
Health
use with caution

[email protected] low health (35/100) — consider alternatives

  • Low health score (35/100)
Health breakdown0 – 100
5/25
maintenance
3/20
popularity
25/25
security
0/15
maturity
2/15
community
Vulnerabilities
0
none known

Health History

Dependency Tree

License Audit

Dependencies (4)
statsMASSMatrixgraphics
API access

Get this data programmatically — free, no authentication.

curl https://depscope.dev/api/check/cran/hrqglas

First published · 2025-06-12 19:49:44

Last updated · 2025-06-12T18:10:05+00:00