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Sampling the Dirichlet mixture model with slices

Walker, Stephen G. (2007) Sampling the Dirichlet mixture model with slices. Communications in Statistics - Simulation and Computation, 36 (1). pp. 45-54. ISSN 0361-0918. (doi:10.1080/03610910601096262) (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:3777)

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.
Official URL:
http://dx.doi.org/10.1080/03610910601096262

Abstract

We provide a new approach to the sampling of the well known mixture of Dirichlet process model. Recent attention has focused on retention of the random distribution function in the model, but sampling algorithms have then suffered from the countably infinite representation these distributions have. The key to the algorithm detailed in this article, which also keeps the random distribution functions, is the introduction of a latent variable which allows a finite number, which is known, of objects to be sampled within each iteration of a Gibbs sampler.

Item Type: Article
DOI/Identification number: 10.1080/03610910601096262
Uncontrolled keywords: Bayesian nonparametrics; density estimation; Dirichlet process; Gibbs sampler; slice sampling
Subjects: Q Science > QA Mathematics (inc Computing science) > QA276 Mathematical statistics
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Mathematics, Statistics and Actuarial Science
Depositing User: Maureen Cook
Date Deposited: 30 Jun 2008 10:34 UTC
Last Modified: 16 Nov 2021 09:42 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/3777 (The current URI for this page, for reference purposes)

University of Kent Author Information

Walker, Stephen G..

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