- 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...
Expand abstract - Publication status:
- Published
- Peer review status:
- Peer reviewed
- Version:
- Publisher's version
- Publisher copy:
- 10.1214/17-EJS1247
-
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- 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
- Copyright holder:
- Bochkina and Rousseau
- Copyright date:
- 2017
- Notes:
- © 2017 Bochkina and Rousseau. Creative Commons Attribution 4.0 International License.
Journal article
Adaptive density estimation based on a mixture of Gammas
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