Online trend estimation and detection of deviations
Katherine B. Ensor, Julia Schedler, Thomas Sun, Rebecca Schneider, Anthony Mulenga, Jingjing Wu, Lauren B. Stadler, Loren Hopkins
medRxiv 2023.10.26.23297635; doi: https://doi.org/10.1101/2023.10.26.23297635
This website provides details on the application of the state-space modeling and statistical process control frameworks to the time series of Sars-cov2 viral load for various sampling sites in the City of Houston.
The purpose of this analysis is to develop a method that
compares series from two different sampling sites
accounts for measurement error
is comparable to the existing B-spline method employed by the City.
Intended audience: those who wish to replicate the analyses demonstrated here on their own WW epi data.
ability to interpret algebraic equations
basic familiarity with R programming
- Suggested external learning resource: R for Data Science 2E by Hadley Wickham, Mine Çetinkaya-Rundel, and Garrett Grolemund.
an understanding of linear regression
- Suggested external learning resource: Chapter 7 of Introduction to Modern Statistics by Mine Çetinkaya-Rundel and Johanna Hardin.
a willingness to learn some basic time series techniques.
Suggested external learning resource: Time Series: A Data Analysis Approach Using R by Robert Shumway and David Stoffer.
Suggested external learning resource: Forecasting: Principles and Practice 3E by Rob J Hyndman and George Athanasopoulos.