def negative_binomial_logp(mu, alpha, value):
"""Generates symbolic negative binomial logp.
Args:
mu: negative binomial mean tensor
alpha: negative binomial over-dispersion tensor
value: negative binomial counts
Note:
`mu`, `alpha` and `value` must be either shape-compatible or be commensurately broadcastable.
Returns:
symbolic negative binomial logp
"""
return pm_dist_math.bound(pm_dist_math.binomln(value + alpha - 1, value)
+ pm_dist_math.logpow(mu / (mu + alpha), value)
+ pm_dist_math.logpow(alpha / (mu + alpha), alpha),
mu > 0, value >= 0, alpha > 0)
def negative_binomial_logp(mu, alpha, value):
"""Generates symbolic negative binomial logp.
Args:
mu: negative binomial mean tensor
alpha: negative binomial over-dispersion tensor
value: negative binomial counts
Note:
`mu`, `alpha` and `value` must be either shape-compatible or be commensurately broadcastable.
Returns:
symbolic negative binomial logp
"""
return pm_dist_math.bound(pm_dist_math.binomln(value + alpha - 1, value)
+ pm_dist_math.logpow(mu / (mu + alpha), value)
+ pm_dist_math.logpow(alpha / (mu + alpha), alpha),
mu > 0, value >= 0, alpha > 0)