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Stein's method for discrete Gibbs measures

Abstract:

Stein's method provides a way of bounding the distance of a probability distribution to a target distribution $\mu$. Here we develop Stein's method for the class of discrete Gibbs measures with a density $e^V$, where $V$ is the energy function. Using size bias couplings, we treat an example of Gibbs convergence for strongly correlated random variables due to Chayes and Klein [Helv. Phys. Acta 67 (1994) 30--42]. We obtain estimates of the approximation to a grand-canonical Gibbs ensemble. As s...

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Publication status:
Published

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Publisher copy:
10.1214/07-AAP0498

Authors


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Institution:
University of Oxford
Division:
MPLS
Department:
Statistics
Role:
Author
Journal:
Annals of Applied Probability
Volume:
18
Issue:
4
Pages:
1588-1618
Publication date:
2008-08-21
DOI:
EISSN:
1050-5164
ISSN:
1050-5164
Language:
English
Keywords:
Pubs id:
pubs:97526
UUID:
uuid:a870d22b-4f17-44ba-8478-2a9ab3d51e5e
Local pid:
pubs:97526
Source identifiers:
97526
Deposit date:
2012-12-19

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