- Title
- Posterior predictive arguments in favor of the Bayes-Laplace prior as the consensus prior for binomial and multinomial parameters
- Creator
- Tuyl, Frank; Gerlach, Richard; Mengersen, Kerrie
- Relation
- Bayesian Analysis Vol. 4, Issue 1, p. 151-158
- Publisher Link
- http://dx.doi.org/10.1214/09-BA405
- Publisher
- International Society for Bayesian Analysis (ISBA)
- Resource Type
- journal article
- Date
- 2009
- Description
- It is argued that the posterior predictive distribution for the binomial and multinomial distributions, when viewed via a hypergeometric-like representation, suggests the uniform prior on the parameters for these models. The argument is supported by studying variations on an example by Fisher, and complements Bayes' original argument for a uniform prior predictive distribution for the binomial. The fact that both arguments lead to invariance under transformation is also discussed.
- Subject
- Bayesian inference; binomial distribution; invariance; noninformative priors; Jeffreys prior
- Identifier
- uon:6955
- Identifier
- http://hdl.handle.net/1959.13/925283
- Identifier
- ISSN:1936-0975
- Reviewed
- Hits: 1174
- Visitors: 1145
- Downloads: 0
Thumbnail | File | Description | Size | Format |
---|