DummyInitialObservationPrior.coefficient_mean#

DummyInitialObservationPrior.coefficient_mean(context)[source]#

Zero: this prior’s content is entirely in its row.

With infinite variance the component has zero precision, so in a composition its mean is never weighted and the base prior’s centre is untouched.

Parameters:

context (_PriorContext) – The sample description; width and k_endog are read.

Return type:

NDArray[double]

Returns:

A (width, k) array of zeros.

Example

>>> import numpy as np
>>> from cultivars.bayes.priors import PriorContext
>>> ctx = PriorContext(
...     k_endog=2, order=1, scales=np.ones(2), presample_mean=np.zeros(2)
... )
>>> DummyInitialObservationPrior().coefficient_mean(ctx).shape
(3, 2)