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Statistical inference and model selection for the 1861 Hagelloch measles epidemic.

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Statistical inference and model selection for the 1861 Hagelloch measles epidemic. / Neal, Peter J.; Roberts, Gareth O.
In: Biostatistics, Vol. 5, No. 2, 04.2004, p. 249-261.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

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Neal PJ, Roberts GO. Statistical inference and model selection for the 1861 Hagelloch measles epidemic. Biostatistics. 2004 Apr;5(2):249-261. doi: 10.1093/biostatistics/5.2.249

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Neal, Peter J. ; Roberts, Gareth O. / Statistical inference and model selection for the 1861 Hagelloch measles epidemic. In: Biostatistics. 2004 ; Vol. 5, No. 2. pp. 249-261.

Bibtex

@article{9c365395876444f581102000ccda84d6,
title = "Statistical inference and model selection for the 1861 Hagelloch measles epidemic.",
abstract = "A stochastic epidemic model is proposed which incorporates heterogeneity in the spread of a disease through a population. In particular, three factors are considered: the spatial location of an individual's home and the household and school class to which the individual belongs. The model is applied to an extremely informative measles data set and the model is compared with nested models, which incorporate some, but not all, of the aforementioned factors. A reversible jump Markov chain Monte Carlo algorithm is then introduced which assists in selecting the most appropriate model to fit the data.",
keywords = "Model choice, Reversible jump MCMC, Stochastic epidemics.",
author = "Neal, {Peter J.} and Roberts, {Gareth O.}",
year = "2004",
month = apr,
doi = "10.1093/biostatistics/5.2.249",
language = "English",
volume = "5",
pages = "249--261",
journal = "Biostatistics",
issn = "1468-4357",
publisher = "Oxford University Press",
number = "2",

}

RIS

TY - JOUR

T1 - Statistical inference and model selection for the 1861 Hagelloch measles epidemic.

AU - Neal, Peter J.

AU - Roberts, Gareth O.

PY - 2004/4

Y1 - 2004/4

N2 - A stochastic epidemic model is proposed which incorporates heterogeneity in the spread of a disease through a population. In particular, three factors are considered: the spatial location of an individual's home and the household and school class to which the individual belongs. The model is applied to an extremely informative measles data set and the model is compared with nested models, which incorporate some, but not all, of the aforementioned factors. A reversible jump Markov chain Monte Carlo algorithm is then introduced which assists in selecting the most appropriate model to fit the data.

AB - A stochastic epidemic model is proposed which incorporates heterogeneity in the spread of a disease through a population. In particular, three factors are considered: the spatial location of an individual's home and the household and school class to which the individual belongs. The model is applied to an extremely informative measles data set and the model is compared with nested models, which incorporate some, but not all, of the aforementioned factors. A reversible jump Markov chain Monte Carlo algorithm is then introduced which assists in selecting the most appropriate model to fit the data.

KW - Model choice

KW - Reversible jump MCMC

KW - Stochastic epidemics.

U2 - 10.1093/biostatistics/5.2.249

DO - 10.1093/biostatistics/5.2.249

M3 - Journal article

VL - 5

SP - 249

EP - 261

JO - Biostatistics

JF - Biostatistics

SN - 1468-4357

IS - 2

ER -