QVARResult._summary_table#
- QVARResult._summary_table()[source]#
Build the structured summary.
- Return type:
- Returns:
One row per equation with its own first-lag coefficient at the lowest and highest estimated levels and its
R1at the lowest; the metadata lists the levels; the notes state the check-loss nature of the fit and its absent likelihood, the largest companion root across levels, the crossing share, the reduced-form reading ofirf, the one-step forecast rule, and the absence of standard errors.
Example
>>> import numpy as np >>> y = np.random.default_rng(0).standard_normal((120, 2)) >>> table = QVAR(y, order=1).fit(quantiles=(0.1, 0.5, 0.9))._summary_table() >>> table.title, len(table.rows), len(table.notes) ('QVAR(1) Results', 2, 6) >>> table.columns ('equation', 'own L1 (tau=0.1)', 'own L1 (tau=0.9)', 'R1 (tau=0.1)') >>> table.metadata[1] ('Levels', '0.1, 0.5, 0.9') >>> QVAR(y, order=0).fit(quantiles=(0.5,))._summary_table().rows[0][1:3] ('-', '-')