Create a random variable for JohnsonSU.

See JohnsonSU for more details.


Original Docstring for Distribution

Construct Johnson's SU distributions.

The distributions have shape parameteres tailweight and skewness, mean loc, and scale scale.

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

skewness Floating-point Tensor. Skewness of the distribution(s).
tailweight Floating-point Tensor. Tail weight of the distribution(s). tailweight 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 any of skewness, tailweight, loc and scale are different dtypes.