Hidden markov models with discrete and continuous hidden states and various emission distributions
Hidden markov models are models of a sequence of random variables, where the hidden state models the dynamics and observations are generated at each time step.
hmms : -> base : -> base.py : base class -> filter.py : forward recursion -> smooth.py : backward recursion -> gaussian_hmm : discrete hidden states -> linear_gaussian_hmm : continous hidden state