Implements fast algorithms for kernel quantile regression and related models, including non-crossing kernel quantile regression and regularized linear quantile regression. The methods are described in Tang, Gu and Wang (2026) <doi:10.1080/10618600.2025.2541004>.
| Version: | 1.0.1 |
| Depends: | R (≥ 3.5.0) |
| Imports: | stats, parallel |
| Suggests: | knitr, rmarkdown |
| Published: | 2026-07-01 |
| DOI: | 10.32614/CRAN.package.fastkqr |
| Author: | Qian Tang [aut, cre], Yuwen Gu [aut], Boxiang Wang [aut] |
| Maintainer: | Qian Tang <qian-tang at uiowa.edu> |
| License: | GPL-2 |
| NeedsCompilation: | yes |
| Materials: | NEWS |
| CRAN checks: | fastkqr results |
| Reference manual: | fastkqr.html , fastkqr.pdf |
| Vignettes: |
Getting Started with fastkqr (source, R code) |
| Package source: | fastkqr_1.0.1.tar.gz |
| Windows binaries: | r-devel: fastkqr_1.0.1.zip, r-release: fastkqr_1.0.1.zip, r-oldrel: fastkqr_1.0.1.zip |
| macOS binaries: | r-release (arm64): fastkqr_1.0.1.tgz, r-oldrel (arm64): fastkqr_1.0.1.tgz, r-release (x86_64): fastkqr_1.0.1.tgz, r-oldrel (x86_64): fastkqr_1.0.1.tgz |
| Old sources: | fastkqr archive |
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