Statistical inference for epidemic processes in a homogeneous community (Part IV of the book Stochastic Epidemic Models and Inference)
arXiv:2004.07688 · doi:10.1007/978-3-030-30900-8
Abstract
This document is the Part IV of the book 'Stochastic Epidemic Models with Inference' edited by Tom Britton and Etienne Pardoux. It is written by Catherine Larédo, with the contribution of Viet Chi Tran for the Chapter 4. Epidemic data present challenging statistical problems, starting from the recurrent issue of handling missing information. We review methods such as MCMC, ABC or methods based on diffusion approximations. Plan of this document: 1) Observations and Asymptotic Frameworks; 2) Inference for Markov Chain Epidemic Models; 3) Inference Based on the Diffusion Approximation of Epidemic Models; 4) Inference for Continuous Time SIR models.
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Cited by in corpus (11)
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- Stochastic epidemics in a heterogeneous community (Part III of the book Stochastic Epidemic Models and Inference)
- Statistical inference for epidemic processes in a homogeneous community (Part IV of the book Stochastic Epidemic Models and Inference)
- A probabilistic framework for particle-based reaction-diffusion dynamics using classical Fock space representations
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- Stochastic approach to epidemic spreading
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