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RLadyBug——一个用于随机流行病模型的R包。

RLadyBug-An R package for stochastic epidemic models.

作者信息

Höhle Michael, Feldmann Ulrike

机构信息

Department of Statistics, University of Munich, Ludwigstr. 33, 80539 Munich, Germany.

出版信息

Comput Stat Data Anal. 2007 Oct 15;52(2):680-686. doi: 10.1016/j.csda.2006.11.016. Epub 2006 Dec 4.

DOI:10.1016/j.csda.2006.11.016
PMID:32287569
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7114252/
Abstract

RLadyBug is an S4 package for the simulation, visualization and estimation of stochastic epidemic models in R. Maximum likelihood and Bayesian inference can be performed to estimate the parameters in a susceptible-exposed-infectious-recovered (SEIR) model, which is a stochastic model for describing a single outbreak of an infectious disease. The package is thus one step towards statistical software supporting parameter estimation, calculation of confidence intervals and hypothesis testing for transmission models.

摘要

RLadyBug是一个用于在R中对随机流行病模型进行模拟、可视化和估计的S4软件包。可以进行最大似然估计和贝叶斯推断,以估计易感-暴露-感染-康复(SEIR)模型中的参数,该模型是用于描述传染病单次爆发的随机模型。因此,该软件包朝着支持传播模型参数估计、置信区间计算和假设检验的统计软件迈出了一步。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2efd/7114252/2ba9f8c74f69/gr6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2efd/7114252/9e8261f46f41/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2efd/7114252/ba34f0981f59/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2efd/7114252/6fa9cb8dd465/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2efd/7114252/3446f1ca7bfe/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2efd/7114252/e54e21f7b388/gr5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2efd/7114252/2ba9f8c74f69/gr6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2efd/7114252/9e8261f46f41/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2efd/7114252/ba34f0981f59/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2efd/7114252/6fa9cb8dd465/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2efd/7114252/3446f1ca7bfe/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2efd/7114252/e54e21f7b388/gr5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2efd/7114252/2ba9f8c74f69/gr6.jpg

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Real-time epidemiology: Understanding the spread of SARS.实时流行病学:了解非典的传播
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