'The Anscombe residuals
Parameters
endog : array
The endogenous response variable
mu : array
The inverse of the link function at the linear predicted values.
iweights : array-like
1d array of frequency weights. The default is 1.
scale : float, optional
An optional argument to divide the residuals by sqrt(scale).
The default is 1.
See Also
statsmodels.genmod.families.family.Family : `resid_anscombe` for the
individual families for more information
Notes
Anscombe residuals are defined by
.. math::
resid\_anscombe_i = \frac{A(y)-A(\mu)}{A\'(\mu)\sqrt{Var[\mu]}}
where :math:`A\'(y)=v(y)^{-\frac{1}{3}}` and :math:`v(\mu)` is the
variance function :math:`Var[y]=\frac{\phi}{w}v(mu)`.
The transformation :math:`A(y)` makes the residuals more normal
distributed.'

def resid_anscombe(self, endog, mu, iweights=1.0, scale=1.0):

    raise NotImplementedError
