GraphicalVARResult._summary_table#

GraphicalVARResult._summary_table()[source]#

Build the structured summary.

Return type:

SummaryTable

Returns:

One row per variable with its Granger out-degree and in-degree (support at threshold 0) and its contemporaneous degree (partial correlations above 0.05); the metadata carries the dimensions and both edge counts; the notes state the two networks’ sizes, how each was estimated, how an edge is to be read, and that no inference is reported.

Example

>>> import numpy as np
>>> rng = np.random.default_rng(0)
>>> y = np.zeros((300, 4))
>>> for t in range(1, 300):
...     y[t] = 0.5 * y[t - 1] + rng.standard_normal(4)
>>> table = GraphicalVAR(y, order=1).fit(seed=0)._summary_table()
>>> table.title, table.columns[:2]
('Graphical VAR(1) Results', ('variable', 'out-degree'))
>>> len(table.rows), len(table.notes), table.metadata[0]
(4, 4, ('Model', 'Graphical VAR(1)'))