pymc.dims.Poisson#

class pymc.dims.Poisson(name, *dist_params, dims=None, initval=None, observed=None, total_size=None, transform=UNSET, default_transform=UNSET, model=None, **kwargs)[source]#

Poisson distribution.

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)

../../../_images/pymc-dims-Poisson-1.png

Support

\(x \in \mathbb{N}_0\)

Mean

\(\mu\)

Variance

\(\mu\)
Parameters:
muxtensor_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, **kwargs)