STVARResult._regime_sigma#
- STVARResult._regime_sigma(regime)[source]#
The common innovation covariance, whichever regime is named.
- Parameters:
regime (
Literal['lower','upper']) –"lower"or"upper"; ignored, since the smooth model estimates one covariance.- Return type:
- Returns:
sigma_u.
Example
>>> import numpy as np >>> y = np.random.default_rng(0).standard_normal((200, 2)) >>> res = STVAR(y, order=1, transition_variable="y1").fit() >>> res._regime_sigma("lower") is res._regime_sigma("upper") is res.sigma_u True