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Activity Number: 254 - Contributed Poster Presentations: Section on Bayesian Statistical Science
Type: Contributed
Date/Time: Monday, July 29, 2019 : 2:00 PM to 3:50 PM
Sponsor: Section on Bayesian Statistical Science
Abstract #307075
Title: Bayesian Quantile Envelope Model
Author(s): Minji Lee* and Saptarshi Chakraborty and Zhihua Su
Companies: University of Florida and Memorial Sloan Kettering Cancer Center and University of Florida
Keywords: envelope model; Bayesian quantile regression; sufficient dimension reduction

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.

Authors who are presenting talks have a * after their name.

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