Registration is open for TensorFlow Dev Summit 2020 Learn more

tfp.edward2.CholeskyLKJ

View source on GitHub

Create a random variable for CholeskyLKJ.

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

See CholeskyLKJ for more details.

Returns:

RandomVariable.

Original Docstring for Distribution

Construct CholeskyLKJ distributions.

Args:

  • dimension: Python int. The dimension of the correlation matrices to sample.
  • concentration: float or double Tensor. The positive concentration parameter of the CholeskyLKJ distributions.
  • 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.

Raises:

  • ValueError: If dimension is negative.