Intercept

class pymc_marketing.terms.Intercept(name='intercept', prior=<factory>)

GLM-style intercept term; same as Parameter with a default name.

Intercept is provided for familiar GLM notation. It is identical to Parameter in behavior and lifecycle. Use Parameter when the role is not an intercept (e.g. a cohort scale or product effect).

Parameters:

namestr

Name for the PyMC variable. Defaults to "intercept".

priorVariableFactory

Prior distribution. Any VariableFactory is accepted.

Methods

Intercept.__init__([name, prior])
Intercept.add_coords(ds)	Add coordinates to the model during register_data.
Intercept.create_variable()	Build a free parameter variable.
Intercept.from_dict(data)	Reconstruct a parameter from its serialized form.
Intercept.get_coords(ds)	Collect coordinates from prior.dims present in the dataset.
Intercept.register_data(ds)	Register shared data variables as pmd.Data.
Intercept.set_data(ds[, model])	Update shared data variables for out-of-sample prediction.
Intercept.to_dict([_orig])

Attributes

Intercept.data_vars	Dataset variables this term reads as shared data.
Intercept.frozen_deterministics	Deterministics this term freezes for out-of-sample evaluation.
Intercept.name
Intercept.prior