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Normal approximation for the posterior in exponential families

Abstract:

In this paper we obtain quantitative Bernstein-von Mises type bounds on the normal approximation of the posterior distribution in exponential family models when centering either around the posterior mode or around the maximum likelihood estimator. Our bounds, obtained through a version of Stein's method, are non-asymptotic, and data dependent; they are of the correct order both in the total variation and Wasserstein distances, as well as for approximations for expectations of smooth functions...

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Publication status:
Not published
Peer review status:
Not peer reviewed

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Publisher copy:
10.48550/arXiv.2209.08806

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Institution:
University of Oxford
Division:
MPLS
Department:
Statistics
Role:
Author
ORCID:
0000-0002-0363-9470
Publisher:
arXiv / Cornell University
Publication date:
2022-09-19
DOI:
Language:
English
Keywords:
Pubs id:
1280379
Local pid:
pubs:1280379
Deposit date:
2022-11-25

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