generalized_additive_models.Exponential

class generalized_additive_models.Exponential(scale=1)

Exponential Distribution

__init__(scale=1)

Methods

V(mu)
V_derivative(mu)
__init__([scale])
deviance(*, y, mu[, sample_weight, scaled])
get_metadata_routing()	Get metadata routing of this object.
get_params([deep])	Get parameters for this estimator.
sample(mu[, size, random_state])
set_params(**params)	Set the parameters of this estimator.
to_scipy(mu)
variance(mu)	Var(Y) = V(mu) * scale

Attributes

domain
name
scale

V(mu)

V_derivative(mu)

deviance(*, y, mu, sample_weight=None, scaled=True)

domain = (0, inf)

name = 'exponential'

scale = 1

to_scipy(mu)

variance(mu)

Var(Y) = V(mu) * scale