VARXResult.params#

property VARXResult.params: dict[str, float][source]#

Every coefficient, keyed "{equation}: {regressor}".

Example

>>> import numpy as np
>>> rng = np.random.default_rng(0)
>>> y, x = rng.standard_normal((120, 2)), rng.standard_normal((120, 1))
>>> res = VARX(y, x, order=1, names=("a", "b"), exog_names=("z",)).fit()
>>> list(res.params)[:4], len(res.params)
(['a: const', 'a: a.L1', 'a: b.L1', 'a: z'], 8)
>>> res.params.keys() == res.bse.keys()
True