Bayesian single-index quantile regression for ordinal data
Rahim Alhamzawi, Haithem Taha Mohammad Ali · Communications in Statistics - Simulation and Computation · 2018
A Bayesian single-index quantile estimation approach for ordinal data is proposed. A simple and efficient MCMC algorithm was developed for posterior computation using a normal-exponential mixture representation of the skewed Laplace distribution. The proposed method is then demonstrated via simulated studies and two real data sets. Results show that the proposed method performs well under the simulated studies and real data analysis.