A Bayesian Approach to Quantile Envelope Regression (306554)Saptarshi Chakraborty, Memorial Sloan Kettering Cancer Center
*Minji Lee, University of Florida
Zhihua Su, University of Florida
Keywords: quantile regression, dimension reduction, Bayesian approach, envelope model
We propose a Bayesian quantile envelope model that adapts a nascent construct called envelope in Bayesian perspective. The Bayesian quantile envelope model can achieve the efficiency gains compared to the standard Bayesian quantile model. We provide a simple block Metropolis-within-Gibbs MCMC sampler for applications. We also demonstrate that our method performs well through simulations and data analysis.