Journal article
Sufficientness postulates for Gibbs-type priors and hierarchical generalizations
- Abstract:
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A fundamental problem in Bayesian nonparametrics consists of selecting a prior distribution by assuming that the corresponding predictive probabilities obey certain properties. An early discussion of such a problem, although in a parametric framework, dates back to the seminal work by English philosopher W. E. Johnson, who introduced a noteworthy characterization for the predictive probabilities of the symmetric Dirichlet prior distribution. This is typically referred to as Johnson's "suff...
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- Publication status:
- Published
- Peer review status:
- Peer reviewed
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(Version of record, pdf, 258.5KB)
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- Publisher copy:
- 10.1214/17-STS619
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Authors
Funding
Bibliographic Details
- Publisher:
- Institute of Mathematical Statistics (IMS) Publisher's website
- Journal:
- Statistical Science Journal website
- Volume:
- 32
- Issue:
- 4
- Pages:
- 487-500
- Publication date:
- 2017-11-28
- Acceptance date:
- 2017-06-10
- DOI:
- EISSN:
-
2168-8745
- ISSN:
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0883-4237
- Source identifiers:
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701409
Item Description
- Keywords:
- Pubs id:
-
pubs:701409
- UUID:
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uuid:101ed398-9c63-4ffe-8c3c-ce2eb52bb2c1
- Local pid:
- pubs:701409
- Deposit date:
- 2017-06-20
Terms of use
- Copyright holder:
- Institute of Mathematical Statistics
- Copyright date:
- 2017
- Notes:
- This is the version of record following peer review of the article. The final version is also available online from the Institute of Mathematical Statistics at: 10.1214/17-STS619
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