Bayesian Melding Estimation of a Stochastic SEIR Model

被引：17
|
作者：
Hotta, Luiz K. [1 ,2 ]
机构：
[1] Univ Estadual Campinas, Dept Stat, Campinas, SP, Brazil
[2] Univ Estadual Campinas, Dept Stat, BR-13083970 Campinas, SP, Brazil
来源：
MATHEMATICAL POPULATION STUDIES | 2010年 / 17卷 / 02期
基金：
巴西圣保罗研究基金会;
关键词：
Bayesian inference; Bayesian melding; HIV/TB interaction; SEIR model estimation; stochastic epidemic models; stochastic SEIR model; STATISTICAL-INFERENCE; INFECTION; HIV; TUBERCULOSIS; EBOLA;
D O I：
10.1080/08898481003689528
中图分类号：
C921 [人口统计学];
学科分类号：
摘要：
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.
引用
收藏
页码：101 / 111
页数：11
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