Create a random variable for BetaBinomial.

See BetaBinomial for more details.


Original Docstring for Distribution

Initialize a batch of BetaBinomial distributions.

total_count Non-negative integer-valued tensor, whose dtype is the same as concentration1 and concentration0. The shape is broadcastable to [N1,..., Nm] with m >= 0. When total_count is broadcast with concentration1 and concentration0, it defines the distribution as a batch of N1 x ... x Nm different Beta-Binomial distributions. Its components should be equal to integer values.
concentration1 Positive floating-point Tensor indicating mean number of successes. Specifically, the expected number of successes is total_count * concentration1 / (concentration1 + concentration0).
concentration0 Positive floating-point Tensor indicating mean number of failures; see description of concentration1 for details.
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.