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Abstract Details
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Activity Number:
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119
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Type:
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Topic Contributed
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Date/Time:
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Monday, August 1, 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 - #300686 |
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Title:
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Direct Sampling
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Author(s):
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Paul Damien*+
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Companies:
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The University of Texas at Austin
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Address:
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1 University Station - B6000, Austin, TX, 78712-1178,
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Keywords:
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Rejection Sampling ;
Auxiliary Variable ;
Bernstein Polynomial
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Abstract:
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In recent years, Markov chain Monte Carlo (MCMC) methods have been used to provide a full Bayesian analysis when the posterior distribution of interest is both analytically intractable, and it is not known how to draw independent samples. In this paper, a non-MCMC approach to sampling from posterior distributions is developed and illustrated. Some sampling problems, now thought to be best handled by MCMC methods alone, are tackled efficiently via independent samples.
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