Package: hdqr 1.0.1
Qian Tang
hdqr: Fast Algorithm for Penalized Quantile Regression
Implements an efficient algorithm to fit and tune penalized quantile regression models using the generalized coordinate descent algorithm. Designed to handle high-dimensional datasets effectively, with emphasis on precision and computational efficiency. This package implements the algorithms proposed in Tang, Q., Zhang, Y., & Wang, B. (2022) <https://openreview.net/pdf?id=RvwMTDYTOb>.
Authors:
hdqr_1.0.1.tar.gz
hdqr_1.0.1.tar.gz(r-4.5-noble)hdqr_1.0.1.tar.gz(r-4.4-noble)
hdqr_1.0.1.tgz(r-4.4-emscripten)hdqr_1.0.1.tgz(r-4.3-emscripten)
hdqr.pdf |hdqr.html✨
hdqr/json (API)
| # Install 'hdqr' in R: |
| install.packages('hdqr', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 28 days agofrom:827283bd3b. Checks:2 OK. Indexed: no.
| Target | Result | Latest binary |
|---|---|---|
| Doc / Vignettes | OK | Feb 12 2025 |
| R-4.5-linux-x86_64 | OK | Feb 12 2025 |
Exports:cv.hdqrcv.nc.hdqrhdqrnc.hdqr
