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

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