'The logistic cumulative distribution function
Parameters
X : array-like
`X` is the linear predictor of the logit model.  See notes.
Returns
1/(1 + exp(-X))
Notes
In the logit model,
.. math:: \Lambda\left(x^{\prime}\beta\right)=\text{Prob}\left(Y=1|x\right)=\frac{e^{x^{\prime}\beta}}{1+e^{x^{\prime}\beta}}'

def cdf(self, X):

    X = np.asarray(X)
    return (1 / (1 + np.exp((- X))))
