# --------------------------------------------
# CITATION file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
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cff-version: 1.2.0
message: 'To cite package "bayesQR" in publications use:'
type: software
license: GPL-2.0-or-later
title: 'bayesQR: Bayesian Quantile Regression'
version: '2.4'
doi: 10.18637/jss.v076.i07
identifiers:
- type: doi
  value: 10.32614/CRAN.package.bayesQR
abstract: Bayesian quantile regression using the asymmetric Laplace distribution,
  both continuous as well as binary dependent variables are supported. The package
  consists of implementations of the methods of Yu & Moyeed (2001) <https://doi.org/10.1016/S0167-7152(01)00124-9>,
  Benoit & Van den Poel (2012) <https://doi.org/10.1002/jae.1216> and Al-Hamzawi,
  Yu & Benoit (2012) <https://doi.org/10.1177/1471082X1101200304>. To speed up the
  calculations, the Markov Chain Monte Carlo core of all algorithms is programmed
  in Fortran and called from R.
authors:
- family-names: Benoit
  given-names: Dries F.
  email: Dries.Benoit@UGent.be
- family-names: Benoit
  given-names: Dries F.
- family-names: Al-Hamzawi
  given-names: Rahim
- family-names: Yu
  given-names: Keming
- family-names: Poel
  given-names: Dirk
  name-particle: Van den
preferred-citation:
  type: article
  title: 'bayesQR: A Bayesian Approach to Quantile Regression'
  authors:
  - family-names: Benoit
    given-names: Dries F.
    email: Dries.Benoit@UGent.be
  - family-names: Poel
    given-names: Dirk
    name-particle: Van den
  journal: Journal of Statistical Software
  year: '2017'
  volume: '76'
  issue: '7'
  doi: 10.18637/jss.v076.i07
  start: '1'
  end: '32'
repository: https://ugent-cvamo.r-universe.dev
commit: 4549ee7f902ca19ea79d417b4f79304600c85120
date-released: '2023-09-08'
contact:
- family-names: Benoit
  given-names: Dries F.
  email: Dries.Benoit@UGent.be