ConditionalForecastResult._summary_table#

ConditionalForecastResult._summary_table()[source]#

Build the structured summary: mean paths, conditioned cells marked.

One row per horizon and series with the unconditional mean, the conditional mean, the 16-84% band, and a star on conditioned cells; the notes read the modesty statistic, say whether the bands carry parameter uncertainty, and restate that conditions are hard.

Return type:

SummaryTable

Returns:

The SummaryTable that summary(), str(), and the notebook renderer display.

Example

>>> import numpy as np
>>> from cultivars.multivariate.reduced_form.vector_autoregression import VAR
>>> y = np.random.default_rng(0).standard_normal((120, 2))
>>> res = VAR(y, order=1).fit()
>>> scenario = conditional_forecast(res, 2, {"y1": [0.5]}, n_draws=50, seed=0)
>>> table = scenario._summary_table()
>>> table.columns
('h', 'series', 'unconditional', 'conditional', '16-84%', '')
>>> table.rows[0][1], table.rows[0][3], table.rows[0][5], table.rows[1][5]
('y1', '0.5000', '*', '')