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Create a random variable for BetaBinomial.
tfp.edward2.BetaBinomial( *args, **kwargs )
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
concentration0. The shape is broadcastable to
m >= 0. When
total_countis broadcast with
concentration0, it defines the distribution as a batch of
N1 x ... x Nmdifferent Beta-Binomial distributions. Its components should be equal to integer values.
concentration1: Positive floating-point
Tensorindicating mean number of successes. Specifically, the expected number of successes is
total_count * concentration1 / (concentration1 + concentration0).
concentration0: Positive floating-point
Tensorindicating mean number of failures; see description of
Truedistribution parameters are checked for validity despite possibly degrading runtime performance. When
Falseinvalid inputs may silently render incorrect outputs.
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.
strname prefixed to Ops created by this class.