# pymc.Poisson#

class pymc.Poisson(name, *args, **kwargs)[source]#

Poisson log-likelihood.

Often used to model the number of events occurring in a fixed period of time when the times at which events occur are independent. The pmf of this distribution is

$f(x \mid \mu) = \frac{e^{-\mu}\mu^x}{x!}$
 Support $$x \in \mathbb{N}_0$$ Mean $$\mu$$ Variance $$\mu$$
Parameters
mu

Expected number of occurrences during the given interval (mu >= 0).

Notes

The Poisson distribution can be derived as a limiting case of the binomial distribution.

Methods

 Poisson.__init__(*args, **kwargs) Poisson.dist(mu, *args, **kwargs) Creates a tensor variable corresponding to the cls distribution. Poisson.moment(size, mu)

Attributes

 rv_op