'The logistic probability density function
Parameters
X : array-like
`X` is the linear predictor of the logit model.  See notes.
Returns
pdf : ndarray
The value of the Logit probability mass function, PMF, for each
point of X. ``np.exp(-x)/(1+np.exp(-X))**2``
Notes
In the logit model,
.. math:: \lambda\left(x^{\prime}\beta\right)=\frac{e^{-x^{\prime}\beta}}{\left(1+e^{-x^{\prime}\beta}\right)^{2}}'

def pdf(self, X):

    X = np.asarray(X)
    return (np.exp((- X)) / ((1 + np.exp((- X))) ** 2))
