VECMXResult._trailing_labels#

VECMXResult._trailing_labels()[source]#

Contemporaneous exogenous differences, then the error-correction terms.

Example

>>> import numpy as np
>>> rng = np.random.default_rng(0)
>>> x = np.cumsum(rng.standard_normal((200, 1)), axis=0)
>>> y = x + rng.standard_normal((200, 1))
>>> VECMX(y, x, order=1, rank=1).fit()._trailing_labels()
('D.x1', 'ec1')
>>> VECMX(y, x, order=1, rank=1, contemporaneous=False).fit()._trailing_labels()
('ec1',)
Return type:

tuple[str, ...]