Brq: an R package for Bayesian quantile regression

Rahim Alhamzawi () and Haithem Taha Mohammad Ali
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Rahim Alhamzawi: University of Al-Qadisiyah
Haithem Taha Mohammad Ali: Nawroz University

METRON, 2020, vol. 78, issue 3, No 4, 313-328

Abstract: Abstract Bayesian regression quantile has received much attention in recent literature. The objective of this paper is to illustrate Brq, a new software package in R. Brq allows for the Bayesian coefficient estimation and variable selection in regression quantile (RQ) and support Tobit and binary RQ. In addition, this package implements the Bayesian Tobit and binary RQ with lasso and adaptive lasso penalties. Further modeling functions for summarising the results, drawing trace plots, posterior histograms, autocorrelation plots, and plotting quantiles are included.

Keywords: Bayesian quantile; Lasso; Adaptive lasso; Prior elicitation; Tobit (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (3)

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DOI: 10.1007/s40300-020-00190-6

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