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).

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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
ePrint ID: 29968
Date Deposited: 12 May 2006
Last Modified: 27 Mar 2014 18:18
Contact Email Address: J.J.Forster@soton.ac.uk
URI: http://eprints.soton.ac.uk/id/eprint/29968

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