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Activity Number: 601 - Prior Specifications for Finite Bayesian Mixture Models
Type: Invited
Date/Time: Thursday, August 2, 2018 : 8:30 AM to 10:20 AM
Sponsor: International Society for Bayesian Analysis (ISBA)
Abstract #326554 Presentation
Title: Jeffreys Priors and Alternative Noninformative Solutions for Location-Scale Mixtures
Author(s): Christian Robert* and Clara Grazian
Companies: Universite Paris-Dauphine and University of Oxford
Keywords: mixtures; Bayesian Analysis; Jeffreys priors; non-informative priors

While Jeffreys priors usually are defined for the parameters of mixtures of distributions, they are not available in closed form. Furthermore, they often are improper priors. We study in this talk the implementation and the properties of Jeffreys priors in several mixture settings, show that the associated posterior distributions are most often improper, and then propose different non-informative alternatives for the analysis of location-scale mixtures.

Authors who are presenting talks have a * after their name.

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