'Derivative of the logit transform
Parameters
p: array-like
Probabilities
Returns
g\'(p) : array
Value of the derivative of logit transform at `p`
Notes
g\'(p) = 1 / (p * (1 - p))
Alias for `Logit`:
logit = Logit()'

def deriv(self, p):

    p = self._clean(p)
    return (1.0 / (p * (1 - p)))
