bbqr: Bayesian Quantile Regression with Lasso and Adaptive Lasso

Markov chain Monte Carlo samplers for Bayesian quantile regression, based on the asymmetric Laplace distribution and the location-scale mixture representation of Kozumi and Kobayashi (2011) <doi:10.1080/00949655.2010.496117>. A binary response and an observed continuous response are both supported, each with three penalty layers behind one interface: no penalty, following Benoit and Van den Poel (2012) <doi:10.1002/jae.1216>; the Bayesian lasso, following Benoit, Al-Hamzawi and Yu (2013) <doi:10.1007/s00180-013-0439-0>; and the Bayesian adaptive lasso of Rubio Garcia (2023) <https://soar.wichita.edu/entities/publication/a2f86232-4704-4ec2-b685-751e7b04ec42>. In the binary family each is available as published and in a corrected form, the default, in which every improper prior component is replaced by a proper one so that the posterior exists unconditionally; the continuous family ships the corrected form only. The continuous adaptive-lasso layer at its default reproduces the penalty of Alhamzawi, Yu and Benoit (2012) <doi:10.1177/1471082X1101200304>. A binary threshold model identifies the coefficient vector only up to a positive scale, so the binary samplers expose the identification anchor as an explicit argument, allowing fixing the scale of the error distribution, fixing a single coefficient, and constraining the norm of the coefficient vector to be compared directly; an observed response identifies the scale, so the continuous samplers have no anchor and draw it every sweep. The MCMC cores are written in Fortran and called from R.

Version:	0.1.0
Depends:	R (≥ 4.2)
Imports:	graphics, stats, utils
Suggests:	testthat (≥ 3.0.0), coda, knitr, rmarkdown, quantreg
Published:	2026-09-08
DOI:	10.32614/CRAN.package.bbqr (may not be active yet)
Author:	Fernando Rubio Garcia [aut, cre] (Wichita State University), Dries F. Benoit [ctb, cph] (Author of 'bayesQR', from which the Fortran RNG wrapper and package layout are derived), Rahim Al-Hamzawi [ctb], Keming Yu [ctb], Dirk Van den Poel [ctb]
Maintainer:	Fernando Rubio Garcia <j332v755 at wichita.edu>
BugReports:	https://github.com/fernandorubiogarcia/bbqr/issues
License:	GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
Copyright:	See inst/COPYRIGHTS for the attribution of third-party components inherited from the 'bayesQR' package. bbqr copyright details
URL:	https://github.com/fernandorubiogarcia/bbqr
NeedsCompilation:	yes
Citation:	bbqr citation info
Materials:	NEWS
CRAN checks:	bbqr results

Documentation:

Reference manual:	bbqr.html , bbqr.pdf
Vignettes:	Binary and continuous quantile regression, and the anchor you have to choose (source, R code)

Downloads:

Package source:	bbqr_0.1.0.tar.gz
Windows binaries:	r-devel: not available, r-release: bbqr_0.1.0.zip, r-oldrel: bbqr_0.1.0.zip
macOS binaries:	r-release (arm64): not available, r-oldrel (arm64): not available, r-release (x86_64): bbqr_0.1.0.tgz, r-oldrel (x86_64): bbqr_0.1.0.tgz

Linking:

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