ConditionalForecastResult.conditioned#

property ConditionalForecastResult.conditioned: NDArray[bool][source]#

(steps, k) mask of conditioned cells, ~isnan(conditions).

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, 3, {"y1": [0.0, None, 0.0]}, n_draws=10)
>>> scenario.conditioned
array([[ True, False],
       [False, False],
       [ True, False]])