Create a random variable for StudentT.

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.