Alright, I just saw this Julia code, https://github.com/johncwok/ChangePointDetection.jl , that implements an algorithm called least square density difference (LSDD) method. It is used to detect changepoints in time-series or to infer wether or not two time-series come from the same underlying probability distribution.
Reference
The LSDD method was developped in the article Density-difference estimation from M. Sugiyama, T. Suzuki, T. Kanamori, M. C. du Plessis, S. Liu, and I. Takeuchi. in 2013.
Indicator summary
Alright, I just saw this Julia code, https://github.com/johncwok/ChangePointDetection.jl , that implements an algorithm called least square density difference (LSDD) method. It is used to detect changepoints in time-series or to infer wether or not two time-series come from the same underlying probability distribution.
Reference
The LSDD method was developped in the article Density-difference estimation from M. Sugiyama, T. Suzuki, T. Kanamori, M. C. du Plessis, S. Liu, and I. Takeuchi. in 2013.
http://www.ms.k.u-tokyo.ac.jp/sugi/2013/LSDD.pdf
Codebase
https://github.com/johncwok/ChangePointDetection.jl
Implementation plan
Best to have a look at the code and see if it can be improved performance wise. Probably also integrated with our sliding window viewer.