'Calculates the significance level of the variable tested'

def _compute_sig(self):

    m = self._est_cond_mean()
    Y = self.endog
    X = self.exog
    n = np.shape(X)[0]
    u = (Y - m)
    u = (u - np.mean(u))
    fct1 = ((1 - (5 ** 0.5)) / 2.0)
    fct2 = ((1 + (5 ** 0.5)) / 2.0)
    u1 = (fct1 * u)
    u2 = (fct2 * u)
    r = (fct2 / (5 ** 0.5))
    I_dist = np.empty((self.nboot, 1))
    for j in range(self.nboot):
        u_boot = copy.deepcopy(u2)
        prob = np.random.uniform(0, 1, size=(n, 1))
        ind = (prob < r)
        u_boot[ind] = u1[ind]
        Y_boot = (m + u_boot)
        I_dist[j] = self._compute_test_stat(Y_boot, X)
    sig = 'Not    Significant'
    if (self.test_stat > mquantiles(I_dist, 0.9)):
        sig = '*'
    if (self.test_stat > mquantiles(I_dist, 0.95)):
        sig = '**'
    if (self.test_stat > mquantiles(I_dist, 0.99)):
        sig = '***'
    return sig
