VariableScaling

pydantic model pymc_marketing.mmm.scaling.VariableScaling

Abstract base for scaling a variable.

The scaling through the dimension of 'date' is assumed and doesn’t need to be specified.

Concrete subclasses:

• DataDerivedScaling – scale by a statistic of the data ("max" or "mean"), computed at fit time.

• FixedScaling – use a user-supplied constant that stays the same across model refreshes.

Methods

VariableScaling.__init__(**data)	Create a new model by parsing and validating input data from keyword arguments.
VariableScaling.from_dict(data)	Reconstruct from a dict via Pydantic model_validate.
VariableScaling.scaling_description()	Human-readable summary of the scaling strategy (e.g. for logging).
VariableScaling.to_dict()	Serialize to a dict via Pydantic model_dump.

field dims: str | tuple[str, ...] [Required]

The dimensions to perform the operation through ("date" is always included implicitly).