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Activity Number:
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623
- Bayesian Variable Selection
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Type:
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Contributed
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Date/Time:
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Thursday, August 3, 2017 : 8:30 AM to 10:20 PM
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Sponsor:
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Section on Bayesian Statistical Science
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Abstract #324767
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View Presentation
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Title:
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High-Dimensional Sparse Logistic Regression with Fractional Likelihoods
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Author(s):
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Satwik Acharyya* and Anirban Bhattacharya
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Companies:
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Texas A & M University and Texas A&M University
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Keywords:
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Abstract:
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We consider high dimensional logistic regression models from a Bayesian perspective. We work in a fractional likelihood framework and develop shrinkage priors suitable for sparse logistic regression. We develop an efficient Gibbs sampler to fit the model and study theoretical properties in terms posterior concentration rates.
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Authors who are presenting talks have a * after their name.
