Journal article

### Sufficientness postulates for Gibbs-type priors and hierarchical generalizations

Abstract:

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...

Publication status:
Published
Peer review status:
Peer reviewed

### Access Document

Files:
• (Version of record, pdf, 258.5KB)
Publisher copy:
10.1214/17-STS619

### Authors

More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Statistics
Role:
Author
More from this funder
Funding agency for:
Battison, M
Grant:
617071
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:
0883-4237
Source identifiers:
701409
Keywords:
Pubs id:
pubs:701409
UUID:
uuid:101ed398-9c63-4ffe-8c3c-ce2eb52bb2c1
Local pid:
pubs:701409
Deposit date:
2017-06-20