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fastkqr: A Fast Algorithm for Kernel Quantile Regression

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

Documentation:

Reference manual: fastkqr.html , fastkqr.pdf
Vignettes: Getting Started with fastkqr (source, R code)

Downloads:

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

Linking:

Please use the canonical form https://CRAN.R-project.org/package=fastkqr to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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