Lijoi, Antonio, Prunster, Igor, Walker, Stephen G. (2008) Investigating nonparametric priors with Gibbs structure. Statistica Sinica, 18 (4). pp. 1653-1668. ISSN 1017-0405. (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:12612)
The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided. |
Abstract
This paper investigates nonparametric priors that induce infinite Gibbs-type partitions; such a feature is desirable both from a conceptual and a mathematical point of view. Recently it has been shown that Gibbs-type priors, with sigma is an element of (0, 1), are equivalent to sigma-stable Poisson-Kingman models. By looking at solutions to a recursive equation arising through Gibbs partitions, we provide an alternative proof of this fundamental result. Since practical implementation of general sigma-stable Poisson-Kingman models is difficult, we focus on a related class of priors, namely normalized random measures with independent increments; these are easily implementable in complex Bayesian models. We establish the result that the only Gibbs-type priors within this class are those based on a generalized gamma random measure.
Item Type: | Article |
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Uncontrolled keywords: | Bayesian nonparametrics; Gibbs exchangeable partitions; generalized gamma process; normalized random measures with independent increments; recursive equation; stable distribution |
Subjects: | Q Science > QA Mathematics (inc Computing science) |
Divisions: | Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Mathematics, Statistics and Actuarial Science |
Funders: | Engineering and Physical Sciences Research Council (https://ror.org/0439y7842) |
Depositing User: | Judith Broom |
Date Deposited: | 17 Apr 2009 08:41 UTC |
Last Modified: | 05 Nov 2024 09:45 UTC |
Resource URI: | https://kar.kent.ac.uk/id/eprint/12612 (The current URI for this page, for reference purposes) |
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