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Model choice problems using approximate Bayesian computation with applications to pathogen transmission data sets

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  • Xing Ju Lee
  • Christopher C. Drovandi
  • Anthony N. Pettitt

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  • Xing Ju Lee & Christopher C. Drovandi & Anthony N. Pettitt, 2015. "Model choice problems using approximate Bayesian computation with applications to pathogen transmission data sets," Biometrics, The International Biometric Society, vol. 71(1), pages 198-207, March.
    • Handle: RePEc:bla:biomet:v:71:y:2015:i:1:p:198-207
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    File URL: http://hdl.handle.net/10.1111/biom.12249
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    References listed on IDEAS

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    1. C. C. Drovandi & A. N. Pettitt, 2011. "Estimation of Parameters for Macroparasite Population Evolution Using Approximate Bayesian Computation," Biometrics, The International Biometric Society, vol. 67(1), pages 225-233, March.
    2. McKinley Trevelyan & Cook Alex R & Deardon Robert, 2009. "Inference in Epidemic Models without Likelihoods," The International Journal of Biostatistics, De Gruyter, vol. 5(1), pages 1-40, July.
    3. Bull, Shelley B. & Mak, Carmen & Greenwood, Celia M. T., 2002. "A modified score function estimator for multinomial logistic regression in small samples," Computational Statistics & Data Analysis, Elsevier, vol. 39(1), pages 57-74, March.
    4. Tom Britton & Theodore Kypraios & Philip D. O'Neill, 2011. "Inference for Epidemics with Three Levels of Mixing: Methodology and Application to a Measles Outbreak," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 38(3), pages 578-599, September.
    5. N. Friel & A. N. Pettitt, 2008. "Marginal likelihood estimation via power posteriors," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 70(3), pages 589-607, July.
    6. McKinley, Trevelyan J. & Ross, Joshua V. & Deardon, Rob & Cook, Alex R., 2014. "Simulation-based Bayesian inference for epidemic models," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 434-447.
    7. Ioannis Kosmidis & David Firth, 2011. "Multinomial logit bias reduction via the Poisson log-linear model," Biometrika, Biometrika Trust, vol. 98(3), pages 755-759.
    8. C. C. Drovandi & A. N. Pettitt, 2008. "Multivariate Markov Process Models for the Transmission of Methicillin‐Resistant Staphylococcus Aureus in a Hospital Ward," Biometrics, The International Biometric Society, vol. 64(3), pages 851-859, September.
    9. Paul Fearnhead & Dennis Prangle, 2012. "Constructing summary statistics for approximate Bayesian computation: semi-automatic approximate Bayesian computation," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 74(3), pages 419-474, June.
    10. Chris Groendyke & David Welch & David R. Hunter, 2012. "A Network-based Analysis of the 1861 Hagelloch Measles Data," Biometrics, The International Biometric Society, vol. 68(3), pages 755-765, September.
    11. David J. Spiegelhalter & Nicola G. Best & Bradley P. Carlin & Angelika Van Der Linde, 2002. "Bayesian measures of model complexity and fit," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(4), pages 583-639, October.
    12. Mark A. Beaumont & Jean-Marie Cornuet & Jean-Michel Marin & Christian P. Robert, 2009. "Adaptive approximate Bayesian computation," Biometrika, Biometrika Trust, vol. 96(4), pages 983-990.
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    Cited by:

    1. Dehideniya, Mahasen B. & Drovandi, Christopher C. & McGree, James M., 2018. "Optimal Bayesian design for discriminating between models with intractable likelihoods in epidemiology," Computational Statistics & Data Analysis, Elsevier, vol. 124(C), pages 277-297.
    2. Lee, Xing Ju & Hainy, Markus & McKeone, James P. & Drovandi, Christopher C. & Pettitt, Anthony N., 2018. "ABC model selection for spatial extremes models applied to South Australian maximum temperature data," Computational Statistics & Data Analysis, Elsevier, vol. 128(C), pages 128-144.

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