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Empirical dynamic modeling in scikit-learn's style

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skedm

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Scikit Empirical Dynamic Modeling (skedm) can be used as a way to forecast time series, spatio-temporal 2D or 3D arrays, and even discrete spatial arrangements. More importantly, skedm can provide insight into the underlying dynamics of a system, specifically whether a system is nonlinear and deterministic or whether it is dominated by noise.

For a quick explanation of this package, I suggest checking the wikipedia article on nonlinear analysis . Additionally, Dr. Sugihara's lab has produced some good summary videos of the topic:

  1. Time Series and Dynamic Manifolds
  2. Reconstructed Shadow Manifold

For a more complete background, I suggest checking out Nonlinear Analysis by Kantz as well as Practical implementation of nonlinear time series methods: The TISEAN package

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