2e8c36e6b6a2324e38fbb3f604f92e1bf02659c1,pymc3/distributions/discrete.py,Poisson,logp,#Poisson#Any#,200

Before Change

    def logp(self, value):
        mu = self.mu
        return bound(
            logpow(mu, value) - factln(value) - mu,
            mu >= 0, value >= 0)


class NegativeBinomial(Discrete):
    R

After Change

    def logp(self, value):
        mu = self.mu
        log_prob =  bound(
            logpow(mu, value) - factln(value) - mu,
            mu >= 0, value >= 0)
        // Return zero when mu and value are both zero
        return T.switch(1 * T.eq(mu, 0) * T.eq(value, 0),
                        0, log_prob)


class NegativeBinomial(Discrete):
    R

Instances