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Normalized random measures driven by increasing additive processes

Nieto-Barajas, Luis E., Prunster, Igor, Walker, Stephen G. (2004) Normalized random measures driven by increasing additive processes. Annals of Statistics, 32 (6). pp. 2343-2360. ISSN 0090-5364. (doi:10.1214/009053604000000625) (KAR id:10537)


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
DOI/Identification number: 10.1214/009053604000000625
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: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Mathematics, Statistics and Actuarial Science
Depositing User: Judith Broom
Date Deposited: 26 Sep 2008 14:58 UTC
Last Modified: 16 Nov 2021 09:49 UTC
Resource URI: (The current URI for this page, for reference purposes)

University of Kent Author Information

Walker, Stephen G..

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