algorithms.statistics.models.family.varfuncs

Module: algorithms.statistics.models.family.varfuncs

Inheritance diagram for nipy.algorithms.statistics.models.family.varfuncs:

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Classes

Binomial

class nipy.algorithms.statistics.models.family.varfuncs.Binomial(n=1)[source]

Bases: object

Binomial variance function

p = mu / n; V(mu) = p * (1 - p) * n

INPUTS:

n – number of trials in Binomial

__init__(n=1)[source]

Initialize self. See help(type(self)) for accurate signature.

tol = 1e-10
clean(p)[source]

Power

class nipy.algorithms.statistics.models.family.varfuncs.Power(power=1.0)[source]

Bases: object

Power variance function:

V(mu) = fabs(mu)**power

INPUTS:

power – exponent used in power variance function

__init__(power=1.0)[source]

Initialize self. See help(type(self)) for accurate signature.

VarianceFunction

class nipy.algorithms.statistics.models.family.varfuncs.VarianceFunction[source]

Bases: object

Variance function that relates the variance of a random variable to its mean. Defaults to 1.

__init__($self, /, *args, **kwargs)

Initialize self. See help(type(self)) for accurate signature.