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fastkqr: A Fast Algorithm for Kernel Quantile Regression

An efficient algorithm to fit and tune kernel quantile regression models based on the majorization-minimization (MM) method. It can also fit multiple quantile curves simultaneously without crossing.

Version: 1.0.0
Depends: R (≥ 3.5.0), methods
Imports: graphics, grDevices, stats, utils, dotCall64, rlang, MASS, Matrix
Suggests: knitr, rmarkdown
Published: 2024-05-13
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
CRAN checks: fastkqr results

Documentation:

Reference manual: fastkqr.pdf
Vignettes: Getting started with fastkqr

Downloads:

Package source: fastkqr_1.0.0.tar.gz
Windows binaries: r-devel: fastkqr_1.0.0.zip, r-release: fastkqr_1.0.0.zip, r-oldrel: fastkqr_1.0.0.zip
macOS binaries: r-release (arm64): fastkqr_1.0.0.tgz, r-oldrel (arm64): fastkqr_1.0.0.tgz, r-release (x86_64): fastkqr_1.0.0.tgz, r-oldrel (x86_64): fastkqr_1.0.0.tgz

Linking:

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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.