Change Point Detection in Time Series
Sample eBook chapters (free): https://github.com/dataman-git/modern-time-series/blob/main/20240522beauty_TOC.pdf
eBook on Teachable.com: $22.50
https://drdataman.teachable.com/p/home
The print edition on Amazon.com: $65 https://a.co/d/25FVsMx
Suppose you are exercising now and monitoring your heart rate with a digital device. You run for a quarter mile, walk for ten minutes, then run for another quarter mile. The heart rates may resemble the time series in Figure (1). It shows a cluster of high rates, a cluster of low rates, then back to high rates. The abrupt changes in the time series inform us the source object has major activity changes.
A change point in a time series is a point where there are significant structural breaks or shifts in the data that external factors, such as changes in data generation, technology, or consumer behavior may cause. Change point detection (CPD) is important because it helps us to understand and quantify changes. We need to detect them accurately and timely and send out alarms.
