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Abstract Details
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Activity Number:
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532
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Type:
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Roundtables
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Date/Time:
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Wednesday, August 1, 2012 : 12:30 PM to 1:50 PM
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Sponsor:
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Section on Bayesian Statistical Science
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| Abstract - #305651 |
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Title:
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Bayesian Nonparametrics Methods: Practical Issues and Current Frontiers
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Author(s):
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David Dahl*+
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Companies:
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Brigham Young University
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Address:
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Department of Statistics, Provo, 84602, United States
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Keywords:
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Bayesian nonparametrics ;
Dirichlet process mixture models ;
Random partitions ;
Bayesian computations
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Abstract:
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Bayesian nonparametrics methods provide the flexibility of classical nonparametrics within the Bayesian inferential framework built on well-defined probability models. Bayesian nonparametric methods are increasing commonplace, yet practical issues remain. In this roundtable, we will discuss the current state of Bayesian nonparametric inference, including challenges in getting started, computational techniques for scaling up the sample size and dimensionality, choosing among the many formulations, and the current frontiers of methodology development. Come join us to learn and share your ideas!
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Authors who are presenting talks have a * after their name.
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