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Julia library for fitting and analyzing state space models. Provides efficient implementations of various SSMs including the canonical Gaussian LDS (Kalman Filter/Smoother), Poisson LDS, HMMs, etc.

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depasquale-lab/StateSpaceDynamics.jl

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StateSpaceDynamics.jl: A Julia package for probabilistic state space models (SSMs)

SSM-CI codecov

This package implements a number of state-space models in julia. It take inspiration from the SSM package written in python from the Linderman Lab. Currently, the following models are implemented:

  • Mixture Models
    • Gaussian Mixture Models
    • Poisson Mixture Models
    • Binomial Mixture Models
    • Negative Binomial Mixture Models
    • Student's t Mixture Models
  • Hidden Markov Models
    • Gaussian HMMs
    • Poisson HMMs
    • Binomial HMMs
    • Negative Binomial HMMs
    • Autoregressive HMMs (ARHMM)
  • Linear Dynamical Systems
    • Gaussian Linear Dynamical Systems (Kalman Filter)
    • Poisson Linear Dynamical Systems (PLDS)
    • PFLDS
    • Switching Linear Dynamical Systems (SLDS)
    • Recurrent Switching Linear Dynamical Systems (rSLDS)
  • Generalized Linear Models (Not state space models but needed for HMM-GLMs)
    • Gaussian GLMs
    • Poisson GLMs
    • Binomial GLMs
    • Negative Binomial GLMs
  • HMM-GLM's
    • Gaussian HMM-GLMs
    • Poisson HMM-GLMs
    • Bernoulli HMM-GLMs
    • Negative Binomial HMM-GLMs
    • Multinomial HMM-GLMs

We are hoping to add more models in the future. If you have any suggestions, please open an issue.

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Julia library for fitting and analyzing state space models. Provides efficient implementations of various SSMs including the canonical Gaussian LDS (Kalman Filter/Smoother), Poisson LDS, HMMs, etc.

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