tf.contrib.distributions.quadrature_scheme_lognormal_gauss_hermite

tf.contrib.distributions.quadrature_scheme_lognormal_gauss_hermite(
    loc,
    scale,
    quadrature_size,
    validate_args=False,
    name=None
)

Defined in tensorflow/contrib/distributions/python/ops/poisson_lognormal.py.

Use Gauss-Hermite quadrature to form quadrature on positive-reals.

Note: for a given quadrature_size, this method is generally less accurate than quadrature_scheme_lognormal_quantiles.

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.
• 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.
• name: Python str name prefixed to Ops created by this class.

Returns:

• grid: (Batch of) length-quadrature_size vectors representing the log_rate parameters of a Poisson.
• probs: (Batch of) length-quadrature_size vectors representing the weight associate with each grid value.