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On computer-intensive simulation and estimation methods for rare-event analysis in epidemic models

机译:流行病模型罕见事件分析的计算机密集型仿真和估计方法

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This article focuses, in the context of epidemic models, on rare events that may possibly correspond to crisis situations from the perspective of public health. In general, no close analytic form for their occurrence probabilities is available, and crude Monte Carlo procedures fail. We show how recent intensive computer simulation techniques, such as interacting branching particle methods, can be used for estimation purposes, as well as for generating model paths that correspond to realizations of such events. Applications of these simulation-based methods to several epidemic models fitted from real datasets are also considered and discussed thoroughly. Copyright (c) 2015 John Wiley & Sons, Ltd.
机译:本文在流行病模型的背景下,从公共卫生的角度着眼于可能与危机情况相对应的罕见事件。通常,没有关于其出现概率的紧密分析形式,并且粗略的蒙特卡洛过程失败。我们展示了如何使用最新的密集计算机仿真技术(例如相互作用的分支粒子方法)来进行估算,以及生成与此类事件的实现相对应的模型路径。这些基于模拟的方法在从实际数据集中拟合的几种流行病模型中的应用也得到了考虑和讨论。版权所有(c)2015 John Wiley&Sons,Ltd.

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