Package csb :: Package statistics :: Module scalemixture :: Class GammaPrior

Class GammaPrior

                 object --+    
                          |    
          ScaleMixturePrior --+
                              |
         object --+           |
                  |           |
pdf.AbstractDensity --+       |
                      |       |
        pdf.BaseDensity --+   |
                          |   |
                  pdf.Gamma --+
                              |
                             GammaPrior

Gamma prior on mixture weights including a weak gamma prior on its parameter.

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

Instance Methods

__init__(self, alpha=1.0, beta=1.0, hyper_alpha=(4.0, 1.0), hyper_beta=(2.0, 1.0))
x.__init__(...) initializes x; see help(type(x)) for signature source code

array

log_prob(self, x)
Evaluate the logarithm of the probability of observing values x. source code

Inherited from pdf.Gamma: random

Inherited from pdf.AbstractDensity: __call__, __getitem__, __setitem__, __str__, estimate, evaluate, get_params, set_params

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

Class Variables
Inherited from `pdf.Gamma`: `__abstractmethods__`

Properties
AbstractDensity	hyper_alpha
AbstractDensity	hyper_beta
Inherited from `ScaleMixturePrior`: `estimator`, `scale_estimator` Inherited from `pdf.Gamma`: `alpha`, `beta` Inherited from `pdf.AbstractDensity`: `parameters` Inherited from `object`: `__class__`

Method Details

init(self, alpha=1.0, beta=1.0, hyper_alpha=`(`4.0`,` 1.0`)`, hyper_beta=`(`2.0`,` 1.0`)`)
(Constructor)

source code

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

Overrides: object.__init__: (inherited documentation)

log_prob(self, x)

source code

Evaluate the logarithm of the probability of observing values x.

Parameters:

x - values

Returns: array

Overrides: pdf.AbstractDensity.log_prob

(inherited documentation)

Class GammaPrior

__init__(self, alpha=1.0, beta=1.0, hyper_alpha=(4.0, 1.0), hyper_beta=(2.0, 1.0)) (Constructor)

log_prob(self, x)

init(self, alpha=1.0, beta=1.0, hyper_alpha=`(`4.0`,` 1.0`)`, hyper_beta=`(`2.0`,` 1.0`)`)
(Constructor)