# --------------------------------------------
# CITATION file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
# --------------------------------------------
 
cff-version: 1.2.0
message: 'To cite package "hdqr" in publications use:'
type: software
license: GPL-2.0-only
title: 'hdqr: Fast Algorithm for Penalized Quantile Regression'
version: 1.0.1
doi: 10.32614/CRAN.package.hdqr
abstract: Implements an efficient algorithm to fit and tune penalized quantile regression
  models using the generalized coordinate descent algorithm. Designed to handle high-dimensional
  datasets effectively, with emphasis on precision and computational efficiency. This
  package implements the algorithms proposed in Tang, Q., Zhang, Y., & Wang, B. (2022)
  <https://openreview.net/pdf?id=RvwMTDYTOb>.
authors:
- family-names: Tang
  given-names: Qian
  email: qian-tang@uiowa.edu
- family-names: Zhang
  given-names: Yikai
  email: yikai-zhang@uiowa.edu
- family-names: Wang
  given-names: Boxiang
  email: boxiang-wang@uiowa.edu
repository: https://qiantang0326.r-universe.dev
commit: 827283bd3b7f8863b3d73893f83ebceaeac49adc
date-released: '2025-02-05'
contact:
- family-names: Tang
  given-names: Qian
  email: qian-tang@uiowa.edu