classbayespy.nodes.CategoricalMarkovChain(pi, A, states=None, **kwargs)[source]¶
Node for categorical Markov chain random variables.
The node models a Markov chain which has a discrete set of K possible states
and the next state depends only on the previous state and the state
transition probabilities. The graphical model is shown below:
where contains the probabilities for the initial
state and is the state transition probability matrix. It
is possible to have varying in time.
where
This node can be used to construct hidden Markov models by using
Mixture for the emission distribution.
Parameters:
pi (Dirichlet-like node or (...,K)-array) – , probabilities for the first
state. -dimensional Dirichlet.
A (Dirichlet-like node or (K,K)-array or (...,1,K,K)-array or (...,N-1,K,K)-array) – , probabilities for state
transitions. -dimensional Dirichlet with plates (K,) or
(…,1,K) or (…,N-1,K).
states (int, optional) – , the length of the chain.