Markov chain Monte Carlo exact inference for binomial and multinomial logistic regression models


Forster, Jonathan J., McDonald, John W. and Smith, Peter W.F. (2003) Markov chain Monte Carlo exact inference for binomial and multinomial logistic regression models. Statistics and Computing, 13, (2), 169-177. (doi:10.1023/A:1023212726863).

Download

Full text not available from this repository.

Original Publication URL: http://dx.doi.org/10.1023/A:1023212726863

Description/Abstract

We develop Metropolis-Hastings algorithms for exact conditional inference, including goodness-of-fit tests, confidence intervals and residual analysis, for binomial and multinomial logistic regression models. We present examples where the exact results, obtained by enumeration, are available for comparison. We also present examples where Monte Carlo methods provide the only feasible approach for exact inference.

Item Type: Article
ISSNs: 0960-3174 (print)
Related URLs:
Keywords: conditional inference, exact confidence interval, exact test, goodness-of-fit test, logistic regression, markov chain monte carlo, metropolis-hastings algorithm, residual analysis
Subjects: Q Science > QA Mathematics
H Social Sciences > HA Statistics
Divisions: University Structure - Pre August 2011 > Southampton Statistical Sciences Research Institute
University Structure - Pre August 2011 > School of Mathematics > Statistics
University Structure - Pre August 2011 > School of Social Sciences > Social Statistics
ePrint ID: 34319
Date Deposited: 16 May 2006
Last Modified: 27 Mar 2014 18:21
URI: http://eprints.soton.ac.uk/id/eprint/34319

Actions (login required)

View Item View Item