The Library
Efficient Bayesian inference for Gaussian copula regression models
Tools
Tools
Tools
Pitt, Michael K., Chan, David and Kohn, Robert (2006) Efficient Bayesian inference for Gaussian copula regression models. Biometrika, Volume 93 (Number 3). pp. 537-554. doi:10.1093/biomet/93.3.537 ISSN 0006-3444.
Research output not available from this repository.
Request-a-Copy directly from author or use local Library Get it For Me service.
Official URL: http://dx.doi.org/10.1093/biomet/93.3.537
Abstract
A Gaussian copula regression model gives a tractable way of handling a multivariate regression when some of the marginal distributions are non-Gaussian. Our paper presents a general Bayesian approach for estimating a Gaussian copula model that can handle any combination of discrete and continuous marginals, and generalises Gaussian graphical models to the Gaussian copula framework. Posterior inference is carried out using a novel and efficient simulation method. The methods in the paper are applied to simulated and real data.
| Item Type: | Journal Article | ||||
|---|---|---|---|---|---|
| Subjects: | Q Science > QH Natural history > QH301 Biology Q Science > QA Mathematics |
||||
| Divisions: | Faculty of Social Sciences > Economics | ||||
| Journal or Publication Title: | Biometrika | ||||
| Publisher: | Biometrika Trust | ||||
| ISSN: | 0006-3444 | ||||
| Official Date: | September 2006 | ||||
| Dates: |
|
||||
| Volume: | Volume 93 | ||||
| Number: | Number 3 | ||||
| Number of Pages: | 18 | ||||
| Page Range: | pp. 537-554 | ||||
| DOI: | 10.1093/biomet/93.3.537 | ||||
| Status: | Peer Reviewed | ||||
| Publication Status: | Published | ||||
| Access rights to Published version: | Restricted or Subscription Access |
Data sourced from Thomson Reuters' Web of Knowledge
Request changes or add full text files to a record
Repository staff actions (login required)
 |
View Item |
