'Poisson model cumulative distribution function
Parameters
X : array-like
`X` is the linear predictor of the model.  See notes.
Returns
The value of the Poisson CDF at each point.
Notes
The CDF is defined as
.. math:: \exp\left(-\lambda\right)\sum_{i=0}^{y}\frac{\lambda^{i}}{i!}
where :math:`\lambda` assumes the loglinear model. I.e.,
.. math:: \ln\lambda_{i}=X\beta
The parameter `X` is :math:`X\beta` in the above formula.'

def cdf(self, X):

    y = self.endog
    return stats.poisson.cdf(y, np.exp(X))
