- Title
- A method to handle zero counts in the multinomial model
- Creator
- Tuyl, Frank
- Relation
- The American Statistician Vol. 73, Issue 2, p. 151-158
- Publisher Link
- http://dx.doi.org/10.1080/00031305.2018.1444673
- Publisher
- American Statistical Association
- Resource Type
- journal article
- Date
- 2019
- Description
- In the context of an objective Bayesian approach to the multinomial model, Dirichlet(a, …, a) priors with a < 1 have previously been shown to be inadequate in the presence of zero counts, suggesting that the uniform prior (a = 1) is the preferred candidate. In the presence of many zero counts, however, this prior may not be satisfactory either. A model selection approach is proposed, allowing for the possibility of zero parameters corresponding to zero count categories. This approach results in a posterior mixture of Dirichlet distributions and marginal mixtures of beta distributions, which seem to avoid the problems that potentially result from the various proposed Dirichlet priors, in particular in the context of extreme data with zero counts.
- Subject
- Bayesian inference; Bayes-Laplace prior; model and variable selection; objective priors; spike and slab prior
- Identifier
- http://hdl.handle.net/1959.13/1451064
- Identifier
- uon:44084
- Identifier
- ISSN:0003-1305
- Language
- eng
- Reviewed
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