ocpdet
OCPDet is an open-source Python package for online changepoint detection, implementing state-of-the-art algorithms and a novel approach, using a scikit-learn
style API.
This package is the outcome of my Master Thesis at Imperial College London within the MSc in Statistics, Department of Mathematics.
Algorithms implemented in ocpdet are
- CUSUM: Cumulative Sum algorithm, proposed by Page (1954)
- EWMA: Exponentially Weighted Moving Average algorithm, proposed by Roberts (1959)
- Two Sample tests: Nonparametric hypothesis testing for changepoint detection, proposed by Ross et al. (2011)
- Neural Networks: Novel approach based on sequentially learning neural networks, proposed by Hushchyn et al. (2020) and extended to online context (Master Thesis)
Installation
pip install ocpdet
Examples
How to cite this work
Here is a suggestion to cite this GitHub repository:
Victor Khamesi. (2022). ocpdet: A Python package for online changepoint detection in univariate and multivariate data. (Version v0.0.5). Zenodo. https://doi.org/10.5281/zenodo.7632721
And a possible BibTeX entry:
@software{victor_khamesi_2022,
author = {Victor Khamesi},
title = {ocpdet: A Python package for online changepoint detection in univariate and multivariate data.},
month = oct,
year = 2022,
publisher = {Zenodo},
version = {v0.0.5},
doi = {10.5281/zenodo.7632721},
url = {https://doi.org/10.5281/zenodo.7632721}
}
License
The non-software content of this project is licensed under a Creative Commons Attribution 4.0 International License, and the software code is licensed under the BSD-2 Clause license.