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>.
| Version: |
1.0.1 |
| Depends: |
R (≥ 3.5.0) |
| Imports: |
stats, Matrix, methods |
| Suggests: |
knitr, rmarkdown |
| Published: |
2025-02-12 |
| DOI: |
10.32614/CRAN.package.hdqr |
| Author: |
Qian Tang [aut, cre],
Yikai Zhang [aut],
Boxiang Wang [aut] |
| Maintainer: |
Qian Tang <qian-tang at uiowa.edu> |
| License: |
GPL-2 |
| NeedsCompilation: |
yes |
| CRAN checks: |
hdqr results |
Documentation:
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