py311-ssm

Bayesian learning and inference for state space models

This package has fast and flexible code for simulating, learning, and performing inference in a variety of state space models. Currently, it supports: * Hidden Markov Models (HMM) * Auto-regressive HMMs (ARHMM) * Input-output HMMs (IOHMM) * Hidden Semi-Markov Models (HSMM) * Linear Dynamical Systems (LDS) * Switching Linear Dynamical Systems (SLDS) * Recurrent SLDS (rSLDS) * Hierarchical extensions of the above * Partial observations and missing data It supports the following observation models: * Gaussian * Student's * Bernoulli * Poisson * Categorical * Von Mises