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Sampling Truncated Normal, Beta and Gamma Densities

Damien, Paul, Walker, Stephen G. (2001) Sampling Truncated Normal, Beta and Gamma Densities. Journal of Computational and Graphical Statistics, 10 (2). pp. 206-215. ISSN 1061-8600. (doi:10.1198/10618600152627906) (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:10553)

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/10.1198/10618600152627906

Abstract

We consider the Bayesian analysis of constrained parameter and truncated data problems within a Gibbs sampling framework and concentrate on sampling truncated densities that arise as full conditional densities within the context of the Gibbs sampler. In particular, we restrict attention to the normal, beta, and gamma densities. We demonstrate that, in many instances, it is possible to introduce a latent variable which facilitates an easy solution to the problem. We also discuss a novel approach to sampling truncated densities via a “black-box” algorithm, based on the latent variable idea, valid outside of the context of a Gibbs sampler.

Item Type: Article
DOI/Identification number: 10.1198/10618600152627906
Subjects: Q Science > QA Mathematics (inc Computing science)
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Mathematics, Statistics and Actuarial Science
Depositing User: Judith Broom
Date Deposited: 06 Nov 2008 20:44 UTC
Last Modified: 16 Nov 2021 09:49 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/10553 (The current URI for this page, for reference purposes)

University of Kent Author Information

Walker, Stephen G..

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