csb.statistics.scalemixture.GammaPosteriorSampler

Class GammaPosteriorSampler

object --+ | pdf.AbstractEstimator --+ | ScaleMixturePriorEstimator --+ | GammaPosteriorSampler

Instance Methods

__init__(self)
x.__init__(...) initializes x; see help(type(x)) for signature

source code

AbstractDensity

estimate(self, context, data)
Generate samples from the posterior of alpha and beta.

source code

get_scale_estimator(self)
Return an appropriate estimator for the scales of the mixture distribution under this prior.

source code

Inherited from object: __delattr__, __format__, __getattribute__, __hash__, __new__, __reduce__, __reduce_ex__, __repr__, __setattr__, __sizeof__, __str__, __subclasshook__

Class Variables

__abstractmethods__ = frozenset([])

Properties

Inherited from object: __class__

Method Details

init(self)
(Constructor)

source code

x.__init__(...) initializes x; see help(type(x)) for signature

Overrides: object.__init__: (inherited documentation)

estimate(self, context, data)

source code

Generate samples from the posterior of alpha and beta.

For beta the posterior is a gamma distribution and analytically acessible.

The posterior of alpha can not be expressed analytically and is aproximated using adaptive rejection sampling.

Parameters:

context - context distribution
data - sample values

Returns: AbstractDensity

a new distribution, initialized with the estimated parameters

Raises:

EstimationFailureError - if estimation is not possible

Overrides: pdf.AbstractEstimator.estimate

get_scale_estimator(self)

source code

Return an appropriate estimator for the scales of the mixture distribution under this prior.

Overrides: ScaleMixturePriorEstimator.get_scale_estimator: (inherited documentation)

Nested Classes
Inherited from `pdf.AbstractEstimator`: `__metaclass__`

Class GammaPosteriorSampler

__init__(self) (Constructor)

estimate(self, context, data)

get_scale_estimator(self)

init(self)
(Constructor)