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# Class Gamma

source code

         object --+
                  |
    AbstractDensity --+
                      |
            BaseDensity --+
                          |
                         Gamma

Known Subclasses:
  - scalemixture.GammaPrior

Nested Classes
Inherited from `AbstractDensity`: `__metaclass__`

Instance Methods
__init__(self, alpha=1, beta=1) 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
random(self, size=None) Generate random samples from the probability distribution. | source code
Inherited from `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
| __abstractmethods__ = ``frozenset([``])``

Properties
| alpha
| beta
Inherited from `AbstractDensity`: `estimator`, `parameters` Inherited from `object`: `__class__`

Method Details

### __init__(self, alpha=1, beta=1) (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: AbstractDensity.log_prob (inherited documentation)

### random(self, size=None) | source code
Generate random samples from the probability distribution. Parameters: `size` - number of values to sample Overrides: AbstractDensity.random (inherited documentation)

Property Details

### alpha Get Method: unreachable.alpha(self) Set Method: unreachable.alpha(self, value)

### beta Get Method: unreachable.beta(self) Set Method: unreachable.beta(self, value)