Description
Detect Multiple Change Points from Time Series.
Description
Detect the number and locations of change points. The locations can be either exact or in terms of ranges, depending on the available computational resource. The method is based on Jie Ding, Yu Xiang, Lu Shen, Vahid Tarokh (2017) <doi:10.1109/TSP.2017.2711558>.
README.md
The 'offlineChange' R package
Detect Multiple Change Points from Time Series
Getting Started
First install the devtools package
install.packages("devtools")
library("devtools")
Then install this package
install_github('JieGroup/offlineChange')
Using This Package
To see the available function to use, type
ls("package:offlineChange")
A quick guide of package can be found here
Reference Papers
Ding, J., Xiang, Y., Shen, L., & Tarokh, V. (2017). Multiple change point analysis: Fast implementation and strong consistency. IEEE Transactions on Signal Processing, 65(17), 4495-4510. link
J. Ding, "Multi-window method for unsupervised learning," preprint, 2019.
Acknowledgment
This research is funded by the Defense Advanced Research Projects Agency (DARPA) under grant number HR00111890040.