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Characterizing variation of nonparametric random probability measures using the Kullback–Leibler divergence

Abstract:

This work characterizes the dispersion of some popular random probability measures, including the bootstrap, the Bayesian bootstrap, and the Pólya tree prior. This dispersion is measured in terms of the variation of the Kullback–Leibler divergence of a random draw from the process to that of its baseline centring measure. By providing a quantitative expression of this dispersion around the baseline distribution, our work provides insight for comparing different parameterizations of the models...

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Publication status:
Published
Peer review status:
Peer reviewed
Version:
Accepted manuscript

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Publisher copy:
10.1080/02331888.2016.1258072

Authors


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Department:
Oxford, MSD, NDM, Human Genetics Wt Centre
Nieto-Barajas, L More by this author
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Department:
St Annes College
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Funding agency for:
Watson, J
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Funding agency for:
Nieto-Barajas, L
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Publisher:
Taylor & Francis Publisher's website
Journal:
Statistics Journal website
Volume:
51
Issue:
3
Pages:
558-571
Publication date:
2016-11-16
Acceptance date:
2016-07-20
DOI:
EISSN:
1029-4910
ISSN:
0233-1888
Pubs id:
pubs:664450
URN:
uri:48f47373-28e0-49e8-9729-1251b764bd7a
UUID:
uuid:48f47373-28e0-49e8-9729-1251b764bd7a
Local pid:
pubs:664450

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