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Adaptive density estimation based on a mixture of Gammas

Abstract:

We consider the problem of Bayesian density estimation on the positive semiline for possibly unbounded densities. We propose a hierarchical Bayesian estimator based on the gamma mixture prior which can be viewed as a location mixture. We study convergence rates of Bayesian density estimators based on such mixtures.We construct approximations of the local Hölder densities, and of their extension to unbounded densities, to be continuous mixtures of gamma distributions, leading to approximati...

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Publication status:
Published
Peer review status:
Peer reviewed
Version:
Publisher's version

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Publisher copy:
10.1214/17-EJS1247

Authors


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Institution:
University of Oxford
Division:
MPLS Division
Department:
Statistics
Oxford college:
Jesus College
Role:
Author
Publisher:
Institute of Mathematical Statistics Publisher's website
Journal:
Electronic Journal of Statistics Journal website
Volume:
11
Issue:
1
Pages:
916-962
Publication date:
2017-03-05
Acceptance date:
2016-05-01
DOI:
ISSN:
1935-7524
Pubs id:
pubs:735210
URN:
uri:4b390b08-1df1-4ac3-a39c-74792a50ffc0
UUID:
uuid:4b390b08-1df1-4ac3-a39c-74792a50ffc0
Local pid:
pubs:735210

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