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. (The full text of this publication is not available from this repository)

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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
Uncontrolled keywords: Bayesian nonparametrics; density estimation; Dirichlet process; Gibbs sampler; slice sampling
Subjects: Q Science > QA Mathematics (inc Computing science) > QA276 Mathematical statistics
Divisions: Faculties > Science Technology and Medical Studies > School of Mathematics Statistics and Actuarial Science > Statistics
Depositing User: Maureen Cook
Date Deposited: 30 Jun 2008 10:34
Last Modified: 25 Jun 2014 10:44
Resource URI: http://kar.kent.ac.uk/id/eprint/3777 (The current URI for this page, for reference purposes)
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