pymc.Poisson

class pymc.Poisson(name, *args, **kwargs)

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

\[f(x \mid \mu) = \frac{e^{-\mu}\mu^x}{x!}\]

(Source code, png, hires.png, pdf)

Support	\(x \in \mathbb{N}_0\)
Mean	\(\mu\)
Variance	\(\mu\)

Parameters:

mutensor_like of float

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.dist(mu, *args, **kwargs)

Creates a tensor variable corresponding to the cls distribution.