def normalized(self, demeaned=True):
        if demeaned:
            mean_new = np.zeros_like(self.mean)
        else:
            mean_new = self.mean / self.std_sigma
        sigma_new = self.corr
        args = [getattr(self, ea) for ea in self.extra_args]
        return self.__class__(mean_new, sigma_new, *args)
return a normalized distribution where sigma=corr
dataset/ETHPy150Open statsmodels/statsmodels/statsmodels/sandbox/distributions/mv_normal.py/MVElliptical.normalized