prob140.MarkovChain.steady_state

MarkovChain.steady_state()

Finds the stationary distribution of the Markov Chain.

Returns:

Table

Distribution.

Examples

>>> states = ['A', 'B']
>>> transition_matrix = np.array([[0.1, 0.9],
...                               [0.8, 0.2]])
>>> mc = MarkovChain.from_matrix(states, transition_matrix)
>>> mc.steady_state()
Value | Probability
A     | 0.666667
B     | 0.333333