Kolossiatis, Michalis, Griffin, Jim E., Steel, Mark F.J. (2013) On Bayesian nonparametric modelling of two correlated distributions. Statistics and Computing, 23 (1). pp. 1-15. ISSN 0960-3174. (doi:10.1007/s11222-011-9283-7) (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:36079)
| 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/10.1007/s11222-011-9283-7 |
|
| Additional URLs: |
|
Abstract
In this paper, we consider the problem of modelling a pair of related distributions using Bayesian nonparametric methods. A representation of the distributions as weighted sums of distributions is derived through normalisation. This allows us to define several classes of nonparametric priors. The properties of these distributions are explored and efficient Markov chain Monte Carlo methods are developed. The methodology is illustrated on simulated data and an example concerning hospital efficiency measurement.
| Item Type: | Article |
|---|---|
| DOI/Identification number: | 10.1007/s11222-011-9283-7 |
| Uncontrolled keywords: | Dependent Dirichlet process; Markov chain Monte Carlo; Normalised Random Measures; Polya-urn scheme; Split-Merge move |
| Subjects: | Q Science > QA Mathematics (inc Computing science) > QA276 Mathematical statistics |
| Institutional Unit: | Schools > School of Engineering, Mathematics and Physics > Mathematical Sciences |
| Former Institutional Unit: |
Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Mathematics, Statistics and Actuarial Science
|
| Depositing User: | Michalis Kolossiatis |
| Date Deposited: | 06 Nov 2013 18:48 UTC |
| Last Modified: | 20 May 2025 11:35 UTC |
| Resource URI: | https://kar.kent.ac.uk/id/eprint/36079 (The current URI for this page, for reference purposes) |
- Export to:
- RefWorks
- EPrints3 XML
- BibTeX
- CSV
- Depositors only (login required):

https://orcid.org/0000-0002-4828-7368
Altmetric
Altmetric