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