pymc.HurdleNegativeBinomial#
- class pymc.HurdleNegativeBinomial(name, psi, mu=None, alpha=None, p=None, n=None, **kwargs)[source]#
Hurdle Negative Binomial log-likelihood.
The negative binomial distribution describes a Poisson random variable whose rate parameter is gamma distributed.
The difference with ZeroInflatedNegativeBinomial is that the zeros are not inflated, they come from a completely independent process.
The pmf of this distribution is
\[\begin{split}f(x \mid \psi, \mu, \alpha) = \left\{ \begin{array}{l} (1 - \psi) \ \text{if } x = 0 \\ \psi \frac{\text{NegativeBinomialPDF}(x \mid \mu, \alpha))} {1 - \text{NegativeBinomialCDF}(0 \mid \mu, \alpha)} \ \text{if } x=1,2,3,\ldots \end{array} \right.\end{split}\]- Parameters:
- psitensor_like of
float Expected proportion of Negative Binomial draws (0 < psi < 1)
- alphatensor_like of
float Gamma distribution shape parameter (alpha > 0).
- mutensor_like of
float Gamma distribution mean (mu > 0).
- ptensor_like of
float Alternative probability of success in each trial (0 < p < 1).
- ntensor_like of
float Alternative number of target success trials (n > 0)
- psitensor_like of
Methods
HurdleNegativeBinomial.dist(psi[, mu, ...])