code: def load_results_statsmodels_exog(dataset):
      """
      Load data with seasonal terms in `exog`.
  
      Same as load_results_statsmodels() except that the seasonal term is
      provided to :class:`VECM`'s `__init__()` method via the `eoxg` parameter.
      This is to check whether the same results are produced no matter whether
      `exog` or `seasons` is being used.
  
      Parameters
      ----------
      dataset : DataSet
      """
      results_per_deterministic_terms = dict.fromkeys(dataset.dt_s_list)
      endog = data[dataset]
      for dt_s_tup in dataset.dt_s_list:
          det_string = dt_s_tup[0]
          seasons = dt_s_tup[1]
          first_season = dt_s_tup[2]
          if seasons == 0:
              exog = None
          else:
              exog = seasonal_dummies(
                  seasons,
                  len(data[dataset]),
                  first_season,
                  centered=True,
              )
              if "lo" in dt_s_tup[0]:
                  exog = np.hstack(
                      (exog, 1 + np.arange(len(endog)).reshape(-1, 1))
                  )
                  # remove "lo" since it's now already in exog.
                  det_string = det_string[:-2]
          model = VECM(
              endog,
              exog,
              k_ar_diff=3,
              coint_rank=coint_rank,
              deterministic=det_string,
          )
          results_per_deterministic_terms[dt_s_tup] = model.fit(
              method="ml"
          )
      return results_per_deterministic_terms
  
imports: import numpy
  from numpy.testing import assert_, assert_allclose, assert_array_equal, assert_raises, assert_raises_regex
  import pytest
  import statsmodels.datasets.interest_inflation.data
  from statsmodels.tools.testing import assert_equal
  from statsmodels.tsa.vector_ar.tests.JMulTi_results.parse_jmulti_vecm_output import dt_s_tup_to_string, load_results_jmulti, sublists
  from statsmodels.tsa.vector_ar.util import seasonal_dummies
  from statsmodels.tsa.vector_ar.var_model import VARProcess
  from statsmodels.tsa.vector_ar.vecm import VECM, select_coint_rank, select_order
label_desc: Use image node_id 3 for calling a global function with example usage: load_results_statsmodels_exog(dataset) and returns: results_per_deterministic_terms