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A general framework for the parametrization of hierarchical models
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Papaspiliopoulos, Omiros, Roberts, Gareth O. and Skold, Martin (2007) A general framework for the parametrization of hierarchical models. Statistical Science, Vol.22 (No.1). pp. 59-73. doi:10.1214/088342307000000014 ISSN 0883-4237.
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Official URL: http://dx.doi.org/10.1214/088342307000000014
Abstract
In this paper, we describe centering and noncentering methodology as complementary techniques for use in parametrization of broad classes of hierarchical models, with a view to the construction of effective MCMC algorithms for exploring posterior distributions from these models. We give a clear qualitative understanding as to when centering and noncentering work well, and introduce theory concerning the convergence time complexity of Gibbs samplers using centered and noncentered parametrizations. We give general recipes for the construction of noncentered parametrizations, including an auxiliary variable technique called the state-space expansion technique. We also describe partially noncentered methods, and demonstrate their use in constructing robust Gibbs sampler algorithms whose convergence properties are not overly sensitive to the data.
Item Type: | Journal Article | ||||
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Subjects: | Q Science > QA Mathematics | ||||
Divisions: | Faculty of Science, Engineering and Medicine > Science > Statistics | ||||
Journal or Publication Title: | Statistical Science | ||||
Publisher: | American Institute of Mathematical Statistics | ||||
ISSN: | 0883-4237 | ||||
Official Date: | February 2007 | ||||
Dates: |
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Volume: | Vol.22 | ||||
Number: | No.1 | ||||
Number of Pages: | 15 | ||||
Page Range: | pp. 59-73 | ||||
DOI: | 10.1214/088342307000000014 | ||||
Status: | Peer Reviewed | ||||
Publication Status: | Published | ||||
Access rights to Published version: | Restricted or Subscription Access |
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