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), Benoit & Van den Poel (2012) and Al-Hamzawi, Yu & Benoit (2012). To speed up the calculations, the Markov Chain Monte Carlo core of all algorithms is programmed in Fortran and called from R.
To cite bayesQR in publications use:
Benoit DF, Van den Poel D (2017). "bayesQR: A Bayesian Approach to Quantile Regression." Journal of Statistical Software, 76(7), 1–32. (https://doi.org/10.18637/jss.v076.i07).
Corresponding BibTeX entry:
@Article{,
title = {{bayesQR}: A Bayesian Approach to Quantile Regression},
author = {Dries F. Benoit and Dirk {Van den Poel}},
journal = {Journal of Statistical Software},
year = {2017},
volume = {76},
number = {7},
pages = {1--32},
doi = {10.18637/jss.v076.i07},
}