MichaelisMentenSaturation

class pymc_marketing.mmm.components.saturation.MichaelisMentenSaturation(priors=None, prefix=None)

Wrapper around Michaelis-Menten saturation function.

Calls pymc_marketing.mmm.transformers.michaelis_menten() directly. The saturation level is exposed by the underlying function as alpha, so no extra scaling parameter is added at this layer.

Parameters:

alphatensor

Maximum contribution, the asymptote that the response approaches. Default prior: Prior("Gamma", mu=2, sigma=1).

lamtensor

Half-saturation point on the input axis. Default prior: Prior("HalfNormal", sigma=1).

.. plot::

context:

close-figs

import matplotlib.pyplot as plt import numpy as np from pymc_marketing.mmm import MichaelisMentenSaturation

rng = np.random.default_rng(0)

adstock = MichaelisMentenSaturation() prior = adstock.sample_prior(random_seed=rng) curve = adstock.sample_curve(prior) adstock.plot_curve(curve, random_seed=rng) plt.show()

Methods

MichaelisMentenSaturation.__init__([priors, ...])
MichaelisMentenSaturation.apply(x, *[, ...])	Call within a model context.
MichaelisMentenSaturation.from_dict(data)	Reconstruct a saturation transformation from a dict.
MichaelisMentenSaturation.function(x, alpha, ...)	Michaelis-Menten saturation function.
MichaelisMentenSaturation.plot_curve(curve)	Plot curve HDI and samples.
MichaelisMentenSaturation.plot_curve_hdi(curve)	Plot the HDI of the curve.
MichaelisMentenSaturation.plot_curve_samples(curve)	Plot samples from the curve.
MichaelisMentenSaturation.sample_curve([...])	Sample the curve of the saturation transformation given parameters.
MichaelisMentenSaturation.sample_prior([coords])	Sample the priors for the transformation.
MichaelisMentenSaturation.set_dims_for_all_priors(dims)	Set the dims for all priors.
MichaelisMentenSaturation.to_dict([_orig])	Convert the transformation to a dictionary.
MichaelisMentenSaturation.update_priors(priors)	Update the priors for a function after initialization.
MichaelisMentenSaturation.with_default_prior_dims(dims)	Return a copy with default prior dims (dims=None) set to dims instead.
MichaelisMentenSaturation.with_updated_priors(priors)	Return a copy with updated priors.

Attributes

combined_dims	Get the combined dims for all the parameters.
default_priors
function_priors	Get the priors for the function.
model_config	Mapping from variable name to prior for the model.
prefix
priors	Get the priors for the function.
variable_mapping	Mapping from parameter name to variable name in the model.