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Friday, October 4
Fri, Oct 4, 11:45 AM - 1:15 PM
Evergreen I
Speed Session 3

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.