Overview | Quick Start | hdqr() | cv.hdqr() | nc.hdqr() | cv.nc.hdqr() | Methods
Package: hdqr 1.0.2
hdqr: Fast Algorithm for Penalized Quantile Regression
Implements an efficient algorithm for fitting the entire regularization path of quantile regression models with elastic-net penalties using a generalized coordinate descent scheme. The framework also supports SCAD and MCP penalties. It is designed for high-dimensional datasets and emphasizes numerical accuracy 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_1.0.2.tar.gz
hdqr_1.0.2.zip(r-4.7)hdqr_1.0.2.zip(r-4.6)hdqr_1.0.2.zip(r-4.5)
hdqr_1.0.2.tgz(r-4.6-x86_64)hdqr_1.0.2.tgz(r-4.6-arm64)hdqr_1.0.2.tgz(r-4.5-x86_64)hdqr_1.0.2.tgz(r-4.5-arm64)
hdqr_1.0.2.tar.gz(r-4.7-arm64)hdqr_1.0.2.tar.gz(r-4.7-x86_64)hdqr_1.0.2.tar.gz(r-4.6-arm64)hdqr_1.0.2.tar.gz(r-4.6-x86_64)
hdqr_1.0.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
hdqr/json (API)
| # Install 'hdqr' in R: |
| install.packages('hdqr', repos = c('https://qiantang0326.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 from:f8e47249eb. Checks:13 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-arm64 | OK | 183 | ||
| linux-devel-x86_64 | OK | 164 | ||
| source / vignettes | OK | 185 | ||
| linux-release-arm64 | OK | 131 | ||
| linux-release-x86_64 | OK | 137 | ||
| macos-release-arm64 | OK | 135 | ||
| macos-release-x86_64 | OK | 249 | ||
| macos-oldrel-arm64 | OK | 116 | ||
| macos-oldrel-x86_64 | OK | 281 | ||
| windows-devel | OK | 106 | ||
| windows-release | OK | 97 | ||
| windows-oldrel | OK | 323 | ||
| wasm-release | OK | 100 |
Exports:cv.hdqrcv.nc.hdqrhdqrnc.hdqr
