pymc.ZeroInflatedPoisson#
- class pymc.ZeroInflatedPoisson(name, psi, mu, **kwargs)[source]#
Zero-inflated 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
\[\begin{split}f(x \mid \psi, \mu) = \left\{ \begin{array}{l} (1-\psi) + \psi e^{-\mu}, \text{if } x = 0 \\ \psi \frac{e^{-\mu}\mu^x}{x!}, \text{if } x=1,2,3,\ldots \end{array} \right.\end{split}\](
Source code,png,hires.png,pdf)
Parameters#
- psitensor_like of float
Expected proportion of Poisson variates (0 < psi < 1)
- mutensor_like of float
Expected number of occurrences during the given interval (mu >= 0).
Methods
ZeroInflatedPoisson.__init__(*args, **kwargs)ZeroInflatedPoisson.dist(psi, mu, **kwargs)