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Abstract Details
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Activity Number:
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618
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Type:
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Contributed
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Date/Time:
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Thursday, August 4, 2011 : 8:30 AM to 10:20 AM
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Sponsor:
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Section on Bayesian Statistical Science
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| Abstract - #303175 |
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Title:
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Some Hypothesis Tests Based on Polya Trees
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Author(s):
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Yuhui Chen*+ and Timothy Hanson
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Companies:
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University of South Carolina and University of South Carolina
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Address:
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Department of Statistics, Columbia, SC, 29208, U.S.
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Keywords:
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Hypothesis Test ;
Polya Trees
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Abstract:
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Polya tree priors are random probability distributions that are easily centered at standard parametric families, such as the normal. As such, they provide an extremely convenient avenue towards creating parametric/nonparametric test statistic "blends" for common hypotheses such as (a) data arise from a Gaussian distribution, or (b) the data distribution is the same across several subpopulations.
We construct several intuitive test-statistics based on the predictive density from a Polya tree. The small-sample properties of the tests are investigated via simulation and some asymptotic results are presented.
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