'Residuals, normalized to have unit variance.
Returns
An array wresid standardized by the sqrt if scale'

@cache_readonly
def resid_pearson(self):

    if (not hasattr(self, 'resid')):
        raise ValueError('Method    requires    residuals.')
    eps = np.finfo(self.wresid.dtype).eps
    if (np.sqrt(self.scale) < ((10 * eps) * self.model.endog.mean())):
        from warnings import warn
        warn('All    residuals    are    0,    cannot    compute    normed    residuals.', RuntimeWarning)
        return self.wresid
    else:
        return (self.wresid / np.sqrt(self.scale))
