bqror: An R Package for Bayesian Quantile Regression in Ordinal Models

This article describes an R package bqror that estimates Bayesian quantile regression for ordinal models introduced in \citet{Rahman-2016}. The paper classifies into two types and offers computationally efficient, yet simple, MCMC algorithms estimating regression. generic model with more than 3 outcomes (labeled $OR_{I}$ model) is estimated by a combination of Gibbs sampling Metropolis-Hastings algorithm. Whereas exactly $OR_{II}$ using only. In line the literature, we suggest marginal likelihood comparing alternative explain how to calculate same. their estimation procedures are illustrated via multiple simulation studies implemented applications presented also several other functions contained within package, which necessary estimation, inference, assessing fit.