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Vectors of two-parameter Poisson–Dirichlet processes

Leisen, Fabrizio, Lijoi, Antonio (2011) Vectors of two-parameter Poisson–Dirichlet processes. Journal of Multivariate Analysis, 102 (3). pp. 482-495. ISSN 0047-259X. (doi:10.1016/j.jmva.2010.10.008) (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)

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. (Contact us about this Publication)
Official URL
http://dx.doi.org/10.1016/j.jmva.2010.10.008

Abstract

The definition of vectors of dependent random probability measures is a topic of interest in applications to Bayesian statistics. They represent dependent nonparametric prior distributions that are useful for modelling observables for which specific covariate values are known. In this paper we propose a vector of two-parameter Poisson–Dirichlet processes. It is well-known that each component can be obtained by resorting to a change of measure of a ?-stable process. Thus dependence is achieved by applying a Lévy copula to the marginal intensities. In a two-sample problem, we determine the corresponding partition probability function which turns out to be partially exchangeable. Moreover, we evaluate predictive and posterior distributions.

Item Type: Article
DOI/Identification number: 10.1016/j.jmva.2010.10.008
Subjects: H Social Sciences > HA Statistics
Divisions: Faculties > Sciences > School of Mathematics Statistics and Actuarial Science
Faculties > Sciences > School of Mathematics Statistics and Actuarial Science > Statistics
Depositing User: Fabrizio Leisen
Date Deposited: 07 Jun 2014 09:37 UTC
Last Modified: 01 Aug 2019 10:36 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/36526 (The current URI for this page, for reference purposes)
Leisen, Fabrizio: https://orcid.org/0000-0002-2460-6176
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