DynamicNelsonSiegelResult._summary_table

DynamicNelsonSiegelResult._summary_table()

Structured summary rendered by every display path.

One row per factor with its mean, persistence and innovation standard deviation; metadata pairing the sample dimensions with the likelihood, the parameter count and the criteria; notes on the decay and where the curvature loading peaks, the one-step estimator, and the per-maturity measurement noise.

Return type:

SummaryTable

Returns:

The SummaryTable behind summary().

Example

>>> import numpy as np
>>> res = DynamicNelsonSiegelResult(
...     panel=np.zeros((30, 4)), maturities=np.array([1.0, 2.0, 5.0, 10.0]),
...     decay=0.6, decay_fixed=True, mu=np.array([5.0, -1.5, 0.5]),
...     ar=np.array([0.95, 0.9, 0.8]), state_innovation_cov=np.diag([0.04, 0.09, 0.16]),
...     measurement_var=np.full(4, 0.01), factors=np.zeros((30, 3)),
...     factor_cov=np.tile(np.eye(3), (30, 1, 1)), llf=100.0, nobs=30, n_params=16.0,
... )
>>> table = res._summary_table()
>>> table.title, table.columns
('Dynamic Nelson-Siegel Results', ('factor', 'mean', 'persistence', 'innovation sd'))
>>> table.rows[1]
('slope', '-1.5000', '0.9000', '0.3000')
>>> table.notes[0][:45]
'Loading decay lambda = 0.6000 (held fixed); t'