tfp.edward2.Poisson

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Create a random variable for Poisson.

Aliases:

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

See Poisson for more details.

Returns:

RandomVariable.

Original Docstring for Distribution

Initialize a batch of Poisson distributions.

Args:

  • rate: Floating point tensor, the rate parameter. rate must be positive. Must specify exactly one of rate and log_rate.
  • log_rate: Floating point tensor, the log of the rate parameter. Must specify exactly one of rate and log_rate.
  • interpolate_nondiscrete: Python bool. When False, log_prob returns -inf (and prob returns 0) for non-integer inputs. When True, log_prob evaluates the continuous function k * log_rate - lgamma(k+1) - rate, which matches the Poisson pmf at integer arguments k (note that this function is not itself a normalized probability log-density). Default value: True.
  • validate_args: Python bool. When True distribution parameters are checked for validity despite possibly degrading runtime performance. When False invalid inputs may silently render incorrect outputs. Default value: False.
  • allow_nan_stats: Python bool. 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. Default value: True.
  • name: Python str name prefixed to Ops created by this class.

Raises:

  • ValueError: if none or both of rate, log_rate are specified.
  • TypeError: if rate is not a float-type.
  • TypeError: if log_rate is not a float-type.