code: def test_omni_normtest():
      # tests against R fBasics
      from scipy import stats
  
      st_pv_R = np.array(
          [
              [
                  3.994138321207883,
                  -1.129304302161460,
                  1.648881473704978,
              ],
              [
                  0.1357325110375005,
                  0.2587694866795507,
                  0.0991719192710234,
              ],
          ]
      )
  
      nt = omni_normtest(x)
      assert_almost_equal(nt, st_pv_R[:, 0], 14)
  
      st = stats.skewtest(x)
      assert_almost_equal(st, st_pv_R[:, 1], 14)
  
      kt = stats.kurtosistest(x)
      assert_almost_equal(kt, st_pv_R[:, 2], 11)
  
      st_pv_R = np.array(
          [
              [
                  34.523210399523926,
                  4.429509162503833,
                  3.860396220444025,
              ],
              [
                  3.186985686465249e-08,
                  9.444780064482572e-06,
                  1.132033129378485e-04,
              ],
          ]
      )
  
      x2 = x**2
      # TODO: fix precision in these test with relative tolerance
      nt = omni_normtest(x2)
      assert_almost_equal(nt, st_pv_R[:, 0], 12)
  
      st = stats.skewtest(x2)
      assert_almost_equal(st, st_pv_R[:, 1], 12)
  
      kt = stats.kurtosistest(x2)
      assert_almost_equal(kt, st_pv_R[:, 2], 12)
  
imports: import numpy
  import pandas
  from numpy.testing import assert_almost_equal, assert_raises, assert_equal, assert_allclose
  from statsmodels.stats._adnorm import normal_ad
  from statsmodels.stats.stattools import omni_normtest, jarque_bera, durbin_watson, _medcouple_1d, medcouple, robust_kurtosis, robust_skewness
label_desc: Use image node_id 2 for calling a global function with example usage: test_omni_normtest() without return types