Posterior predictive arguments in favor of the Bayes-Laplace prior as the consensus prior for binomial and multinomial parameters

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

		Thumbnail	File	Description	Size	Format