Bayesian non-parametric inference for stochastic epidemic models using Gaussian Processes

@inproceedings{Xu2016BayesianNI,
  title={Bayesian non-parametric inference for stochastic epidemic models using Gaussian Processes},
  author={Xiaoguang Xu and Theodore Kypraios and Philip D. O'Neill},
  booktitle={Biostatistics},
  year={2016}
}
This paper considers novel Bayesian non-parametric methods for stochastic epidemic models. Many standard modeling and data analysis methods use underlying assumptions (e.g. concerning the rate at which new cases of disease will occur) which are rarely challenged or tested in practice. To relax these assumptions, we develop a Bayesian non-parametric approach using Gaussian Processes, specifically to estimate the infection process. The methods are illustrated with both simulated and real data… CONTINUE READING

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