论文标题
统一社区中流行过程的统计推断（书籍的第四部分随机流行模型和推理）
Statistical inference for epidemic processes in a homogeneous community (Part IV of the book Stochastic Epidemic Models and Inference)
论文作者
论文摘要
该文档是Tom Britton和Etienne Pardoux编辑的《随机流行模型》一书的第四部分。它是由凯瑟琳·拉雷多（CatherineLarédo）撰写的，越来越多，越来越性的统计问题构成了越来越大的统计问题，从处理丢失的信息的经常性问题开始。我们回顾基于扩散近似值的MCMC，ABC或方法等方法。本文件的计划：1）观察和渐近框架； 2）推断马尔可夫链流行模型； 3）基于流行模型的扩散近似的推论； 4）推断连续时间SIR模型。
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.
