Vectors of two-parameter Poisson-Dirichlet processes

Fabrizio Leisen and Antonio Lijoi ()
Additional contact information
Fabrizio Leisen: Universidad Carlos III de Madrid
Antonio Lijoi: Department of Economics and Quantitative Methods, University of Pavia, and Collegio Carlo Alberto

No 119, Quaderni di Dipartimento from University of Pavia, Department of Economics and Quantitative Methods

Abstract: The definition of vectors of dependent random probability measures is a topic of interest in applications to Bayesian statistics. They, indeed, 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 s-stable process. Thus dependence is achieved by applying a L´evy 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.

Keywords: Bayesian nonparametric statistics; Bivariate completely random measures; L´evy copula; Partial exchangeability; Poisson-Dirichlet process; Posterior distribution. (search for similar items in EconPapers)
Pages: 24 pages
Date: 2010-07
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://dem-web.unipv.it/web/docs/dipeco/quad/ps/RePEc/pav/wpaper/q119.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:pav:wpaper:119

Access Statistics for this paper

More papers in Quaderni di Dipartimento from University of Pavia, Department of Economics and Quantitative Methods Contact information at EDIRC.
Bibliographic data for series maintained by Paolo Bonomolo ( this e-mail address is bad, please contact ).