Publications by Tony
transmission chain with R {contacts}
传播链是现场行病学中展示传染病传播关系的重要可视化工具。传统关系型数据绘制工具比较繁琐、费时，而R语言中专门有{contacts}包可供调用。 该包可直接用install.packages()安装。 library(tidyverse) #数据处理 library(outbreaks) #获取mers_korea_2015数据集 library(epicontacts) #...
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Oswego epidemic
1940年4月19日，纽约州Oswego县Lycoming村的地方卫生官员向位于Syracuse的区卫生官员报告了一起急性胃肠道疾病爆发。正在接受流行病学培训的A. M. Rubin医生被派到现场进行调查。现将本起疫情调查处理总结报告如下。 1 基本情况 奥斯威戈( Oswego)是美国纽约州奥斯威戈...
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oswego_qmd
目录 1 基本情况 2 疫情概况 3 病例定义 4 流行病学分布特征 4.1 指征病例： 4.2 三间分布 4.2.1 时间分布 4.2.2 空间分布 4.2.3 人群分布 4.3 潜伏期分析 4.3.1 暴露与发病时间序列关系图 4.3.2 潜伏期 4.3.3 暴露与发病时间点线图 4.3.4 发病与暴露因素可视化 5 危险因素分�...
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A case of revealjs
Untitled Quarto Quarto enables you to weave together content and executable code into a finished presentation. To learn more about Quarto presentations see https://quarto.org/docs/presentations/. Bullets When you click the Render button a document will be generated that includes: Content authored with markdown Output from executable code Code W...
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Amazing stat_summary
强大的stat_summary神器 对于tidyverse家族中的stat_family函数的科普贴。 Tony https://rpubs.com (ZSCDC) 2023-07-14 Contents 概述 应用场景 geom_family stat_summary() 解析 数据流 mean_se函数 geom参数 fun.data参数 fun.args 隐藏技能 计算更改条图颜色 计算更改条图宽度 计算更改条图透...
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Amazing stat_summary
强大的stat_summary神器 对于tidyverse家族中的stat_family函数的科普贴。 Tony https://rpubs.com (ZSCDC) 2023-07-13 对于tidyverse家族里的画图大杀器ggplot2，大家更熟悉于geom_*family*函数。但在其中还隐藏着34个stat_族函数。先把其中一个stat_summary拉出来跟大家认识一下。 Distill is ...
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Dynamic Modeling 1: Linear Difference Equations
(This is the first in a series on the use of Graph Algebraic models for Social Science.) Linear Difference models are a hugely important first step in learning Graph Algebraic modeling. That said, linear difference equations are a completely independent thing from Graph Algebra. I’ll get into the Graph algebra stuff in the next post or two,...
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Dynamic Modeling 2: Our First Substantive Model
(This is the second of a series of ongoing posts on using Graph Algebra in the Social Sciences.) First-order linear difference equations are powerful, yet simple modeling tools. They can provide access to useful substantive insights to real-world phenomena. They can have powerful predictive ability when used appropriately. Additionally, the...
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Dynamic Modeling 3: When the first-order difference model doesn’t cut it
Data must be selected carefully. The predictive usefulness of the model is grossly diminished if outliers taint the available data. Figure 1, for instance, shows the Defense spending (as a fraction of the national budget) between 1948 and 1968. Note how the trend curve (as defined by our linear difference model from the last post: see appendi...
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Help! My model fits too well!
This is sort-of related to my sidelined study of graph algebra. I was thinking about data I could apply a first-order linear difference model to, and the stock market came to mind. After all, despite some black swan sized shocks, what better predicts a day’s closing than the previous day’s closing? So, I hunted down the data and graphed ex...
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