MediaMuEffect

class pymc_marketing.mmm.additive_effect.MediaMuEffect(**data)

Effect that applies a media transformation to a data variable.

Parameters:

data_varslist[str]

Names of the media data variables in mmm.xarray_dataset. Typically a single element, e.g. ["media_product"].

media_transformationMediaTransformation

Transformation combining adstock and saturation with configurable order. Its dims must include the channel dimension plus any extra dims (e.g. ("product", "channel")).

channel_dimstr, optional

Name of the channel dimension to aggregate over. Default is "channel".

prefixstr

Prefix for effect variable names.

Methods

MediaMuEffect.__init__(**data)	Create a new model by parsing and validating input data from keyword arguments.
MediaMuEffect.construct([_fields_set])
MediaMuEffect.copy(*[, include, exclude, ...])	Returns a copy of the model.
MediaMuEffect.create_data(mmm)	Set prior dims and register data variables.
MediaMuEffect.create_effect(mmm)	Apply the media transformation, sum over the channel dimension.
MediaMuEffect.dict(*[, include, exclude, ...])
MediaMuEffect.from_dict(data)	Reconstruct from a dict.
MediaMuEffect.from_orm(obj)
MediaMuEffect.idata_groups()	Return supplementary data groups to store in DataTree.
MediaMuEffect.json(*[, include, exclude, ...])
MediaMuEffect.model_parametrized_name(params)	Compute the class name for parametrizations of generic classes.
MediaMuEffect.parse_file(path, *[, ...])
MediaMuEffect.parse_obj(obj)
MediaMuEffect.parse_raw(b, *[, ...])
MediaMuEffect.schema([by_alias, ref_template])
MediaMuEffect.schema_json(*[, by_alias, ...])
MediaMuEffect.set_data(mmm, model, X)	Update pm.Data variables from a new prediction dataset.
MediaMuEffect.to_dict([_orig])	Serialize to a dict via Pydantic model_dump.
MediaMuEffect.update_forward_refs(**localns)
MediaMuEffect.validate(value)

Attributes

contribution_var_name	Name of the posterior deterministic holding this effect's contribution.
effect_dims	Dimensions of this effect (media_transformation.dims minus the channel dimension).
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.
media_transformation
channel_dim
data_vars
prefix