TVPVARResult._summary_table#

TVPVARResult._summary_table()[source]#

Build the structured summary.

Return type:

SummaryTable

Returns:

One row per equation with its own first-lag posterior mean at the first and last estimation dates; the metadata carries the draw bookkeeping, the training split and the state dimension; the notes state the drift against the band width, the largest local companion root, the training-sample convention and the absent likelihood surface.

Example

>>> import numpy as np
>>> y = np.random.default_rng(0).standard_normal((120, 2))
>>> res = TVPVAR(y, order=1, training=30).fit(n_draws=20, n_burn=8, seed=0)
>>> table = res._summary_table()
>>> table.title, table.columns, len(table.rows), len(table.notes)
('TVP-VAR(1) Results', ('equation', 'own L1 at start', 'own L1 at end'), 2, 4)
>>> table.metadata[5], table.metadata[7]
(('Training', '30'), ('State dimension', '6'))