WeeklyFourier

class pymc_marketing.mmm.fourier.WeeklyFourier(**data)

Weekly fourier seasonality.

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

n_orderint

Number of fourier modes to use.

prefixstr, optional

Alternative prefix for the fourier seasonality, by default None or “fourier”

priorPrior | VariableFactory, optional

Prior distribution or VariableFactory for the fourier seasonality beta parameters, by default Prior("Laplace", mu=0, b=1)

namestr, optional

Name of the variable that multiplies the fourier modes, by default None

variable_namestr, optional

Name of the variable that multiplies the fourier modes, by default None

Methods

WeeklyFourier.__init__(**data)	Create a new model by parsing and validating input data from keyword arguments.
WeeklyFourier.apply(dayofperiod[, sum])	Apply fourier seasonality to day of year.
WeeklyFourier.construct([_fields_set])
WeeklyFourier.copy(*[, include, exclude, ...])	Returns a copy of the model.
WeeklyFourier.dict(*[, include, exclude, ...])
WeeklyFourier.from_dict(data)	Deserialize the Fourier seasonality.
WeeklyFourier.from_orm(obj)
WeeklyFourier.get_default_start_date([...])	Get the start date for the Fourier curve.
WeeklyFourier.json(*[, include, exclude, ...])
WeeklyFourier.model_parametrized_name(params)	Compute the class name for parametrizations of generic classes.
WeeklyFourier.parse_file(path, *[, ...])
WeeklyFourier.parse_obj(obj)
WeeklyFourier.parse_raw(b, *[, ...])
WeeklyFourier.plot_curve(curve[, n_samples, ...])	Plot the seasonality for one full period.
WeeklyFourier.plot_curve_hdi(curve[, ...])	Plot full period of the fourier seasonality.
WeeklyFourier.plot_curve_samples(curve[, n, ...])	Plot samples from the curve.
WeeklyFourier.sample_curve(parameters[, ...])	Create full period of the Fourier seasonality.
WeeklyFourier.sample_prior([coords])	Sample the prior distributions.
WeeklyFourier.schema([by_alias, ref_template])
WeeklyFourier.schema_json(*[, by_alias, ...])
WeeklyFourier.serialize_prior()	Serialize the prior distribution.
WeeklyFourier.to_dict([_orig])	Serialize the Fourier seasonality.
WeeklyFourier.update_forward_refs(**localns)
WeeklyFourier.validate(value)

Attributes

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.
nodes	Fourier node names for model coordinates.
days_in_period
n_order
prefix
prior
variable_name