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Jeffreys priors for mixture estimation : properties and alternatives
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Grazian, Clare and Robert, Christian P. (2018) Jeffreys priors for mixture estimation : properties and alternatives. Computational Statistics & Data Analysis, 121 . pp. 149-163. doi:10.1016/j.csda.2017.12.005
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Official URL: https://doi.org/10.1016/j.csda.2017.12.005
Abstract
While Jeffreys priors usually are well-defined for the parameters of mixtures of distributions, they are not available in closed form. Furthermore, they often are improper priors. Hence, they have never been used to draw inference on the mixture parameters. The implementation and the properties of Jeffreys priors in several mixture settings are studied. It is shown that the associated posterior distributions most often are improper. Nevertheless, the Jeffreys prior for the mixture weights conditionally on the parameters of the mixture components will be shown to have the property of conservativeness with respect to the number of components, in case of overfitted mixture and it can be therefore used as a default priors in this context.
| Item Type: | Journal Article | ||||||||
|---|---|---|---|---|---|---|---|---|---|
| Subjects: | Q Science > QA Mathematics | ||||||||
| Divisions: | Faculty of Science > Statistics | ||||||||
| Library of Congress Subject Headings (LCSH): | Bayesian statistical decision theory., Mathematical statistics., Neural networks (Computer science) | ||||||||
| Journal or Publication Title: | Computational Statistics & Data Analysis | ||||||||
| Publisher: | Elsevier Science Ltd | ||||||||
| ISSN: | 0167-9473 | ||||||||
| Official Date: | May 2018 | ||||||||
| Dates: |
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| Date of first compliant deposit: | 11 December 2017 | ||||||||
| Volume: | 121 | ||||||||
| Page Range: | pp. 149-163 | ||||||||
| DOI: | 10.1016/j.csda.2017.12.005 | ||||||||
| Status: | Peer Reviewed | ||||||||
| Publication Status: | Published | ||||||||
| Access rights to Published version: | Restricted or Subscription Access |
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