GaussianBasis#

class pymc_marketing.mmm.events.GaussianBasis(priors=None, prefix=None)[source]#

Gaussian basis transformation.

Methods

`GaussianBasis.__init__`([priors, prefix])
`GaussianBasis.apply`(x[, dims])	Call within a model context.
`GaussianBasis.function`(x, sigma)	Gaussian bump function.
`GaussianBasis.plot_curve`(curve[, n_samples, ...])	Plot curve HDI and samples.
`GaussianBasis.plot_curve_hdi`(curve[, ...])	Plot the HDI of the curve.
`GaussianBasis.plot_curve_samples`(curve[, n, ...])	Plot samples from the curve.
`GaussianBasis.sample_curve`([parameters, days])	Sample the curve of the saturation transformation given parameters.
`GaussianBasis.sample_prior`([coords])	Sample the priors for the transformation.
`GaussianBasis.set_dims_for_all_priors`(dims)	Set the dims for all priors.
`GaussianBasis.to_dict`()	Convert the transformation to a dictionary.
`GaussianBasis.update_priors`(priors)	Update the priors for a function after initialization.

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.