LAD
Large Deviations Anomaly Detection
Univariate implementation of
Large Deviations Anomaly Detection (LAD) for collection of multivariate time series data: Applications to COVID-19 data (Sreelekha Guggilam, Varun Chandola, Abani K. Patra)
Journal of Computational Science 72 (2023) 102101
https://www.sciencedirect.com/science/article/pii/S1877750323001618
https://doi.org/10.1016/j.jocs.2023.102101
At 95 percentile may be one the noisiest algorithm yet.
If threshold is set at 95, will detect step changes, etc.
If threshold is set at 99 will only detect most severe spike/dip/point anomalies.
Fast but noisy.
See the docstrings - https://earthgecko-skyline.readthedocs.io/en/latest/skyline.custom_algorithms.html#module-custom_algorithms.lad
See the custom_algorithm source - https://github.com/earthgecko/skyline/blob/master/skyline/custom_algorithms/lad.py