MarkovSwitchingDFMResult._summary_table#
- MarkovSwitchingDFMResult._summary_table()[source]#
Structured summary rendered by every display path.
One row per series with its loading and idiosyncratic variance; notes with the factor dynamics and regime intercepts, the expected durations and the low-state share, the likelihood approximation, the identification convention and the chronology accessor.
- Return type:
- Returns:
The
SummaryTablebehindsummary().
Example
>>> import numpy as np >>> res = MarkovSwitchingDFMResult( ... panel=np.zeros((80, 3)), series_names=("ip", "emp", "sales"), ... loadings=np.array([1.0, 0.8, 1.2]), idiosyncratic_var=np.full(3, 0.3), ... phi=0.6, sigma_v=0.5, mu=np.array([-1.5, 0.5]), ... regime_transition=np.array([[0.8, 0.2], [0.05, 0.95]]), ... factor=np.zeros(80), filtered_prob=np.full((80, 2), 0.5), ... smoothed_prob=np.tile([0.1, 0.9], (80, 1)), means=np.zeros(3), ... scales=np.ones(3), llf=-100.0, n_params=11, converged=True, ... ) >>> table = res._summary_table() >>> table.title, table.rows[1], dict(table.metadata)["Parameters"] ('Markov-Switching Dynamic Factor Results', ('emp', '0.8000', '0.3000'), '11') >>> table.notes[1][:48] 'Expected durations: 5.0 periods (low), 20.0 (hig'