https://github.com/nickc1/skccm
Convergent Cross Mapping in Scikit Learn's style
https://github.com/nickc1/skccm
Last synced: 19 days ago
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Convergent Cross Mapping in Scikit Learn's style
- Host: GitHub
- URL: https://github.com/nickc1/skccm
- Owner: nickc1
- License: mit
- Created: 2016-04-11T15:41:59.000Z (about 9 years ago)
- Default Branch: master
- Last Pushed: 2020-06-16T19:32:06.000Z (almost 5 years ago)
- Last Synced: 2025-03-05T11:49:06.941Z (about 2 months ago)
- Language: Jupyter Notebook
- Size: 10.5 MB
- Stars: 98
- Watchers: 7
- Forks: 17
- Open Issues: 8
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
- awesome-meteo - skccm
README
skccm
========### [Documentation][ccm-docs]
Scikit Convergent Cross Mapping (skccm) can be used as a way to detect causality
between time series.For a quick explanation of this package, I suggest checking out the [Documentation][ccm-docs] as well as the wikipedia article on [convergent cross mapping][ccm-wiki] . Additionally,
[Dr. Sugihara's lab][sugihara-lab] has produced some good summary videos about the topic:1. [Time Series and Dynamic Manifolds][yt-dynamic-manifolds]
2. [Reconstructed Shadow Manifold][yt-reconstructed-manifolds]
3. [State Space Reconstruction: Convergent Cross Mapping][yt-ccm]For a more complete background, I suggest checking out the following papers:
1. [Detecting Causality in Complex Ecosystems by Sugihara][ccm-paper]
2. [Distinguishing time-delayed causal interactions using convergent cross mapping by Ye][ye-paper]Sugihara also has a good [talk about about Correlation and Causation][causation-talk]
[ccm-docs]: http://skccm.readthedocs.io/en/latest/
[ccm-wiki]: https://www.wikiwand.com/en/Convergent_cross_mapping
[sugihara-lab]: http://deepeco.ucsd.edu/
[yt-dynamic-manifolds]: https://www.youtube.com/watch?v=7ucgQE3SO0o
[yt-reconstructed-manifolds]: https://www.youtube.com/watch?v=rs3gYeZeJcw
[yt-ccm]: https://www.youtube.com/watch?v=NrFdIz-D2yM
[ccm-paper]: http://science.sciencemag.org/content/338/6106/496
[ye-paper]: http://www.nature.com/articles/srep14750
[causation-talk]: https://www.youtube.com/watch?v=uhONGgfx8Do&t=2416s