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pySuStaIn

SuStaIn algorithm in Python, with the option to describe the subtype progression patterns using either the event-based model or the piecewise linear z-score model.

Papers

Dependencies

Parallelisation

  • Added parallelized startpoints

Running different SuStaIn implementations

sustainType can be set to:

  • "mixture_GMM" : SuStaIn with an event-based model progression pattern, with Gaussian mixture modelling of normal/abnormal.
  • "mixture_KDE": SuStaIn with an event-based model progression pattern, with Kernel Density Estimation (KDE) mixture modelling of normal/abnormal.
  • "zscore": SuStaIn with a piecewise linear z-score model progression pattern.

See simrun.py for examples of how to run these different implementations.

SuStaIn Tutorial

See the jupyter notebook for a tutorial on how to use SuStaIn using simulated data.

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Python translation of the Subtype and Stage Inference (SuStaIn) model, including an example using simulated data.

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