Normalized random measures driven by increasing additive processes

Nieto-Barajas, Luis E. and Prunster, Igor and Walker, Stephen G. (2004) Normalized random measures driven by increasing additive processes. Annals of Statistics, 32 (6). pp. 2343-2360. ISSN 0090-5364. (Full text available)

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http://dx.doi.org/10.1214/009053604000000625

Abstract

This paper introduces and studies a new class of nonparametric prior distributions. Random probability distribution functions are constructed via normalization of random measures driven by increasing additive processes. In particular, we present results for the distribution of means under both prior and posterior conditions and, via the use of strategic latent variables, undertake a full Bayesian analysis. Our class of priors includes the well-known and widely used mixture of a Dirichlet process.

Item Type: Article
Uncontrolled keywords: Bayesian nonparametric inference; distribution of means of random probability measures; increasing additive process; Levy measure; mixtures of Dirichlet process
Subjects: Q Science > QA Mathematics (inc Computing science)
Divisions: Faculties > Science Technology and Medical Studies > School of Mathematics Statistics and Actuarial Science > Statistics
Depositing User: Judith Broom
Date Deposited: 26 Sep 2008 14:58
Last Modified: 25 Jun 2014 10:51
Resource URI: http://kar.kent.ac.uk/id/eprint/10537 (The current URI for this page, for reference purposes)
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