StudentBVARResult._replication_notes#

StudentBVARResult._replication_notes()[source]#

The predictive check’s remark on how this result replicates.

Return type:

tuple[str, ...]

Returns:

One sentence naming the innovation law and whether its degrees of freedom are drawn or stated.

Example

>>> import numpy as np
>>> y = np.random.default_rng(0).standard_normal((120, 2))
>>> res = StudentBVAR(y, order=1).fit(df=5.0, n_draws=30, n_burn=10, seed=0)
>>> res._replication_notes()
('Replications draw Student-t innovations with the stated 5 degrees of freedom.',)