def cdf(self, x, **kwds):
        lower = -np.inf * np.ones_like(x)
        #std_sigma = np.sqrt(np.diag(self.sigma))
        upper = (x - self.mean)/self.std_sigma
        return mvstdtprob(lower, upper, self.corr, self.df, **kwds)
        #mvstdtcdf doesn't exist yet
        #return mvstdtcdf(lower, x, self.corr, df, **kwds)
cumulative distribution function
dataset/ETHPy150Open statsmodels/statsmodels/statsmodels/sandbox/distributions/mv_normal.py/MVT.cdf