Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/55353
Type: Artigo
Title: Bayesian melding estimation of a stochastic SEIR model
Author: Hotta, Luiz K.
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.
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.
Subject: Inferência bayesiana
Epidemiologia
Modelos epidemiológicos SEIR
Métodos MCMC (Estatística)
Country: Estados Unidos
Editor: Taylor & Francis
Citation: Mathematical Population Studies. Taylor & Francis Inc, v. 17, n. 2, n. 101, n. 111, 2010.
Rights: fechado
Identifier DOI: 10.1080/08898481003689528
Address: https://www.tandfonline.com/doi/abs/10.1080/08898481003689528
Date Issue: 2010
Appears in Collections:IMECC - Artigos e Outros Documentos

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