MarkovSwitchingVARResult.is_regimewise_stationary

property MarkovSwitchingVARResult.is_regimewise_stationary: bool

Whether every regime is stable read as a linear VAR.

Sufficient for stationarity of the switching process but not necessary: one explosive regime is admissible if it is visited rarely and exited fast, a joint condition on the roots and the chain. A False here is a prompt to check that regime’s expected duration.

Example

>>> import numpy as np
>>> rng = np.random.default_rng(0)
>>> s = np.repeat([0, 1, 0, 1], 100)
>>> y = np.array([[-1.0, -0.5], [1.5, 1.0]])[s] + 0.4 * rng.standard_normal((400, 2))
>>> res = MarkovSwitchingVAR(y, order=1, n_regimes=2).fit(seed=0)
>>> res.is_regimewise_stationary, [view.is_stable for view in res.regimes]
(True, [True, True])