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Create a random variable for StudentT.

    *args, **kwargs

See StudentT for more details.



Original Docstring for Distribution

Construct Student's t distributions.

The distributions have degree of freedom df, mean loc, and scale scale.

The parameters df, loc, and scale must be shaped in a way that supports broadcasting (e.g. df + loc + scale is a valid operation).


  • df: Floating-point Tensor. The degrees of freedom of the distribution(s). df must contain only positive values.
  • loc: Floating-point Tensor. The mean(s) of the distribution(s).
  • scale: Floating-point Tensor. The scaling factor(s) for the distribution(s). Note that scale is not technically the standard deviation of this distribution but has semantics more similar to standard deviation than variance.
  • 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.


  • TypeError: if loc and scale are different dtypes.