NoAdstock#

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

Wrapper around no adstock transformation.

Methods

`NoAdstock.__init__`([l_max, normalize, mode, ...])
`NoAdstock.apply`(x[, dims])	Call within a model context.
`NoAdstock.function`(x)	No adstock function.
`NoAdstock.plot_curve`(curve[, n_samples, ...])	Plot curve HDI and samples.
`NoAdstock.plot_curve_hdi`(curve[, ...])	Plot the HDI of the curve.
`NoAdstock.plot_curve_samples`(curve[, n, ...])	Plot samples from the curve.
`NoAdstock.sample_curve`(parameters[, amount])	Sample the adstock transformation given parameters.
`NoAdstock.sample_prior`([coords])	Sample the priors for the transformation.
`NoAdstock.set_dims_for_all_priors`(dims)	Set the dims for all priors.
`NoAdstock.to_dict`()	Convert the adstock transformation to a dictionary.
`NoAdstock.update_priors`(priors)	Update priors for the no adstock transformation.

Attributes

`combined_dims`	Get the combined dims for all the parameters.
`default_priors`
`function_priors`	Get the priors for the function.
`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.