Bayesian variable and link determination for generalised linear models
Ntzoufras, I., Dellaportas, P. and Forster, J.J. (2003) Bayesian variable and link determination for generalised linear models. Journal of Statistical Planning and Inference, 111, (1-2), 165-180. (doi:10.1016/S0378-3758(02)00298-7).
Download
Full text not available from this repository.
Description/Abstract
In this paper, we describe full Bayesian inference for generalised linear models where uncertainty exists about the structure of the linear predictor, the linear parameters and the link function. Choice of suitable prior distributions is discussed in detail and we propose an efficient reversible jump Markov chain Monte-Carlo algorithm for calculating posterior summaries. We illustrate our method with two data examples.
| Item Type: | Article |
|---|---|
| ISSNs: | 0378-3758 (print) |
| Related URLs: | |
| Keywords: | logistic regression, markov chain monte-carlo, reversible jump |
| Subjects: | Q Science > QA Mathematics |
| Divisions: | University Structure - Pre August 2011 > Southampton Statistical Sciences Research Institute University Structure - Pre August 2011 > School of Mathematics > Statistics |
| Item ID: | 29968 |
| Date Deposited: | 12 May 2006 |
| Last Modified: | 01 Jun 2011 14:12 |
| Contributors: | Ntzoufras, I. (Author) Dellaportas, P. (Author) Forster, J.J. (Author) |
| Date: | 2003 |
| Status: | Published |
| Contact Email Address: | J.J.Forster@soton.ac.uk |
| URI: | http://eprints.soton.ac.uk/id/eprint/29968 |
Actions (login required)
 |
View Item |
