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tfp.edward2.GammaGamma

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Create a random variable for GammaGamma.

Aliases:

tfp.edward2.GammaGamma(
    *args,
    **kwargs
)

See GammaGamma for more details.

Returns:

RandomVariable.

Original Docstring for Distribution

Initializes a batch of Gamma-Gamma distributions.

The parameters concentration and rate must be shaped in a way that supports broadcasting (e.g. concentration + mixing_concentration + mixing_rate is a valid operation).

Args:

  • concentration: Floating point tensor, the concentration params of the distribution(s). Must contain only positive values.
  • mixing_concentration: Floating point tensor, the concentration params of the mixing Gamma distribution(s). Must contain only positive values.
  • mixing_rate: Floating point tensor, the rate params of the mixing Gamma distribution(s). Must contain only positive values.
  • validate_args: Python bool, default False. When True distribution parameters are checked for validity despite possibly degrading runtime performance. When False invalid inputs may silently render incorrect outputs.
  • allow_nan_stats: Python bool, default True. When True, statistics (e.g., mean, mode, variance) use the value "NaN" to indicate the result is undefined. When False, an exception is raised if one or more of the statistic's batch members are undefined.
  • name: Python str name prefixed to Ops created by this class.

Raises:

  • TypeError: if concentration and rate are different dtypes.