Bayesian composite quantile regression for the single-index model
Xiaohui Yuan, Xuefei Xiang, Xinran Zhang · PLoS ONE · 2023
By using a Gaussian process prior and a location-scale mixture representation of the asymmetric Laplace distribution, we develop a Bayesian analysis for the composite quantile single-index regression model. The posterior distributions for the unknown parameters are derived, and the Markov chain Monte Carlo sampling algorithms are also given. The proposed method is illustrated by three simulation examples and a real dataset.