Likelihood Estimation for Stochastic Epidemics with Heterogeneous Mixing Populations

We consider a heterogeneously mixing SIR stochastic epidemic process in populations described by a general graph. Likelihood theory is developed to facilitate statistic inference for the parameters of the model under complete observation. We show that these estimators are asymptotically Gaussian unbiased estimates by using a martingale central limit theorem.

Authors:

• Yilun Shang

Keywords:

• statistic inference
• maximum likelihood
• epidemicmodel
• heterogeneous mixing.

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