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Activity Number:
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460
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Type:
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Topic Contributed
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Date/Time:
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Wednesday, August 1, 2007 : 2:00 PM to 3:50 PM
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Sponsor:
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IMS
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| Abstract - #310113 |
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Title:
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Interweaving Data Augmentation Schemes for Faster MCMC
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Author(s):
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Yaming Yu*+
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Companies:
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University of California, Irvine
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Address:
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346A ICS Bldg One, Irvine, CA, 92697-1250,
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Keywords:
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Data Augmentation ; Missing Data ; MCMC ; GLMM
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Abstract:
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Re-parameterizations, or variable transformations, are known to be a key to efficient implementation of Gibbs sampling or general MCMC algorithms. Rather than focusing on a single parameterization, we advocate the method of interweaving two or more data augmentation schemes and demonstrate the benefit of interweaving two special schemes, sufficient augmentation and ancillary augmentation, in applied settings. This is a continuation of Yu and Meng (2007).
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- The address information is for the authors that have a + after their name.
- Authors who are presenting talks have a * after their name.
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