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tfp.edward2.MultivariateStudentTLinearOperator

Create a random variable for MultivariateStudentTLinearOperator.

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

Defined in python/edward2/interceptor.py.

See MultivariateStudentTLinearOperator for more details.

Returns:

RandomVariable.

Original Docstring for Distribution

Construct Multivariate Student's t-distribution on R^k.

The batch_shape is the broadcast shape between df, loc and scale arguments.

The event_shape is given by last dimension of the matrix implied by scale. The last dimension of loc must broadcast with this.

Additional leading dimensions (if any) will index batches.

Args:

  • df: A positive floating-point Tensor. Has shape [B1, ..., Bb] where b >= 0.
  • loc: Floating-point Tensor. Has shape [B1, ..., Bb, k] where k is the event size.
  • scale: Instance of LinearOperator with a floating dtype and shape [B1, ..., Bb, k, k].
  • validate_args: Python bool, default False. Whether to validate input with asserts. If validate_args is False, and the inputs are invalid, correct behavior is not guaranteed.
  • allow_nan_stats: Python bool, default True. If False, raise an exception if a statistic (e.g. mean/variance/etc...) is undefined for any batch member If True, batch members with valid parameters leading to undefined statistics will return NaN for this statistic.
  • name: The name to give Ops created by the initializer.

Raises:

  • TypeError: if not scale.dtype.is_floating.
  • ValueError: if not scale.is_positive_definite.