Markov chain Monte Carlo exact inference for binomial and multinomial logistic regression models
Markov chain Monte Carlo exact inference for binomial and multinomial logistic regression models
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.
conditional inference, exact confidence interval, exact test, goodness-of-fit test, logistic regression, markov chain monte carlo, metropolis-hastings algorithm, residual analysis
169-177
Forster, Jonathan J.
e3c534ad-fa69-42f5-b67b-11617bc84879
McDonald, John W.
9adae16e-e1e1-4ddf-bf4c-7231ee8c1c8e
Smith, Peter W.F.
961a01a3-bf4c-43ca-9599-5be4fd5d3940
2003
Forster, Jonathan J.
e3c534ad-fa69-42f5-b67b-11617bc84879
McDonald, John W.
9adae16e-e1e1-4ddf-bf4c-7231ee8c1c8e
Smith, Peter W.F.
961a01a3-bf4c-43ca-9599-5be4fd5d3940
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), .
(doi:10.1023/A:1023212726863).
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.
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Published date: 2003
Keywords:
conditional inference, exact confidence interval, exact test, goodness-of-fit test, logistic regression, markov chain monte carlo, metropolis-hastings algorithm, residual analysis
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Statistics
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Local EPrints ID: 34319
URI: http://eprints.soton.ac.uk/id/eprint/34319
ISSN: 0960-3174
PURE UUID: ba36ee3c-035d-44d1-93a3-364cf1af1f47
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Date deposited: 16 May 2006
Last modified: 16 Mar 2024 02:45
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Author:
Jonathan J. Forster
Author:
John W. McDonald
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