MarkovSwitchingARResult.regime_stability#

MarkovSwitchingARResult.regime_stability(regime)[source]#

Companion-eigenvalue verdict for one regime’s autoregressive block.

Parameters:

regime (int) – Regime index in 0..K-1.

Return type:

_StabilityAssessment

Returns:

The _StabilityAssessment for that regime read as a linear autoregression.

Raises:

SpecificationError – If regime is out of range.

Example

>>> import numpy as np
>>> rng = np.random.default_rng(0)
>>> res = MarkovSwitchingAR(rng.standard_normal(300), order=1).fit(seed=0, n_init=2)
>>> res.regime_stability(0).is_stable
True
>>> res.regime_stability(2)
Traceback (most recent call last):
    ...
cultivars.exceptions.SpecificationError: regime must be in 0..1; got 2.