code: def test_conditional_mnlogit_2d():
      df = gen_mnlogit(90)
      model = ConditionalMNLogit.from_formula(
          "y ~ 0 + x1 + x2", groups="g", data=df
      )
      result = model.fit()
  
      # Regression tests
      assert_allclose(
          result.params,
          np.asarray(
              [[0.75592035, -1.58565494], [1.82919869, -1.32594231]]
          ),
          rtol=1e-5,
          atol=1e-5,
      )
      assert_allclose(
          result.bse,
          np.asarray(
              [[0.68099698, 0.70142727], [0.65190315, 0.59653771]]
          ),
          rtol=1e-5,
          atol=1e-5,
      )
  
file_path: statsmodels/statsmodels/discrete/tests/test_conditional.py
imports: import numpy
  from statsmodels.discrete.conditional_models import ConditionalLogit, ConditionalPoisson, ConditionalMNLogit
  from statsmodels.tools.numdiff import approx_fprime
  from numpy.testing import assert_allclose
  import pandas
label_desc: Use image node_id 10 for calling a global function with example usage: test_conditional_mnlogit_2d() without return types