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Bayesian Melding Estimation of a Stochastic SEIR Model

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  • LUIZ HOTTA

Abstract

One of the main problems in estimating stochastic SEIR models is that the data are not completely observed. In this case, the estimation is usually done by least squares or by MCMC. The Bayesian melding method is proposed to estimate SEIR models and to evaluate the likelihood in the presence of incomplete data. The method is illustrated by estimating a model for HIV/TB interaction in the population of a prison.

Suggested Citation

  • Luiz Hotta, 2010. "Bayesian Melding Estimation of a Stochastic SEIR Model," Mathematical Population Studies, Taylor & Francis Journals, vol. 17(2), pages 101-111.
    • Handle: RePEc:taf:mpopst:v:17:y:2010:i:2:p:101-111
    DOI: 10.1080/08898481003689528
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    References listed on IDEAS

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    1. Phenyo E. Lekone & Bärbel F. Finkenstädt, 2006. "Statistical Inference in a Stochastic Epidemic SEIR Model with Control Intervention: Ebola as a Case Study," Biometrics, The International Biometric Society, vol. 62(4), pages 1170-1177, December.
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    1. Artalejo, J.R. & Economou, A. & Lopez-Herrero, M.J., 2015. "The stochastic SEIR model before extinction: Computational approaches," Applied Mathematics and Computation, Elsevier, vol. 265(C), pages 1026-1043.

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