GeometricAdstock#

class pymc_marketing.mmm.components.adstock.GeometricAdstock(l_max=FieldInfo(annotation=int, required=True, description='Maximum lag for the adstock transformation.', metadata=[Gt(gt=0)]), normalize=FieldInfo(annotation=bool, required=False, default=True, description='Whether to normalize the adstock values.'), mode=FieldInfo(annotation=ConvMode, required=False, default=<ConvMode.After: 'After'>, description='Convolution mode.'), priors=FieldInfo(annotation=Union[dict[str, Annotated[Prior, InstanceOf]], NoneType], required=False, default=None, description='Priors for the parameters.'), prefix=FieldInfo(annotation=Union[str, NoneType], required=False, default=None, description='Prefix for the parameters.'))[source]#

Wrapper around geometric adstock function.

For more information, see pymc_marketing.mmm.transformers.geometric_adstock().

(Source code, png, hires.png, pdf)

../../_images/pymc_marketing-mmm-components-adstock-GeometricAdstock-1.png

Methods

`GeometricAdstock.__init__`([l_max, ...])
`GeometricAdstock.apply`(x[, dims])	Called within a model context.
`GeometricAdstock.function`(x, alpha)
`GeometricAdstock.plot_curve`(curve[, ...])	Plot curve HDI and samples.
`GeometricAdstock.plot_curve_hdi`(curve[, ...])	Plot the HDI of the curve.
`GeometricAdstock.plot_curve_samples`(curve[, ...])	Plot samples from the curve.
`GeometricAdstock.sample_curve`(parameters[, ...])	Sample the adstock transformation given parameters.
`GeometricAdstock.sample_prior`([coords])	Sample the priors for the transformation.
`GeometricAdstock.to_dict`()	Convert the adstock transformation to a dictionary.
`GeometricAdstock.update_priors`(priors)	Helper to update the priors for a function after initialization.

Attributes

`default_priors`
`function_priors`
`lookup_name`
`model_config`	Mapping from variable name to prior for the model.
`prefix`
`variable_mapping`	Mapping from parameter name to variable name in the model.