tfp.edward2.PoissonLogNormalQuadratureCompound

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Create a random variable for PoissonLogNormalQuadratureCompound.

Aliases:

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

See PoissonLogNormalQuadratureCompound for more details.

Returns:

RandomVariable.

Original Docstring for Distribution

Constructs the PoissonLogNormalQuadratureCompound`.

Args:

  • loc: float-like (batch of) scalar Tensor; the location parameter of the LogNormal prior.
  • scale: float-like (batch of) scalar Tensor; the scale parameter of the LogNormal prior.
  • quadrature_size: Python int scalar representing the number of quadrature points.
  • quadrature_fn: Python callable taking loc, scale, quadrature_size, validate_args and returning tuple(grid, probs) representing the LogNormal grid and corresponding normalized weight. Default value: quadrature_scheme_lognormal_quantiles.
  • 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 quadrature_grid and quadrature_probs have different base dtype.