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bayesQR: Bayesian Quantile Regression

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) <doi:10.1016/S0167-7152(01)00124-9>, Benoit & Van den Poel (2012) <doi:10.1002/jae.1216> and Al-Hamzawi, Yu & Benoit (2012) <doi: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.

Version: 2.4
Depends: R (≥ 4.2), graphics, methods, stats, utils
Published: 2023-09-08
Author: Dries F. Benoit, Rahim Al-Hamzawi, Keming Yu, Dirk Van den Poel
Maintainer: Dries F. Benoit <Dries.Benoit at UGent.be>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
Citation: bayesQR citation info
In views: Bayesian
CRAN checks: bayesQR results

Documentation:

Reference manual: bayesQR.pdf

Downloads:

Package source: bayesQR_2.4.tar.gz
Windows binaries: r-devel: bayesQR_2.4.zip, r-release: bayesQR_2.4.zip, r-oldrel: bayesQR_2.4.zip
macOS binaries: r-release (arm64): bayesQR_2.4.tgz, r-oldrel (arm64): bayesQR_2.4.tgz, r-release (x86_64): bayesQR_2.4.tgz, r-oldrel (x86_64): bayesQR_2.4.tgz
Old sources: bayesQR archive

Reverse dependencies:

Reverse suggests: bayestestR

Linking:

Please use the canonical form https://CRAN.R-project.org/package=bayesQR 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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