HSGPBase

class pymc_marketing.mmm.hsgp.HSGPBase(**data)

Shared logic between HSGP and HSGPPeriodic.

Methods

HSGPBase.__init__(**data)	Create a new model by parsing and validating input data from keyword arguments.
HSGPBase.construct([_fields_set])
HSGPBase.copy(*[, include, exclude, update, ...])	Returns a copy of the model.
HSGPBase.create_variable(name[, xdist])	Create a variable from configuration.
HSGPBase.deterministics_to_replace(name)	Name of the Deterministic variables that are replaced with pm.Flat for out-of-sample.
HSGPBase.dict(*[, include, exclude, ...])
HSGPBase.from_orm(obj)
HSGPBase.json(*[, include, exclude, ...])
HSGPBase.model_parametrized_name(params)	Compute the class name for parametrizations of generic classes.
HSGPBase.parse_file(path, *[, content_type, ...])
HSGPBase.parse_obj(obj)
HSGPBase.parse_raw(b, *[, content_type, ...])
HSGPBase.plot_curve(curve[, n_samples, ...])	Plot the curve.
HSGPBase.register_data(X)	Register the data to be used in the model.
HSGPBase.sample_prior([coords])	Sample from the prior distribution.
HSGPBase.schema([by_alias, ref_template])
HSGPBase.schema_json(*[, by_alias, ref_template])
HSGPBase.to_dict()	Convert the object to a dictionary.
HSGPBase.update_forward_refs(**localns)
HSGPBase.validate(value)

Attributes

model_computed_fields
model_config	Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].
model_extra	Get extra fields set during validation.
model_fields
model_fields_set	Returns the set of fields that have been explicitly set on this model instance.
m
X
X_mid
dims
transform
demeaned_basis