code: def load_results_statsmodels(dataset):
      results_per_deterministic_terms = dict.fromkeys(dt_s_list)
      for dt_s_tup in dt_s_list:
          endog = data[dataset]
          exog = generate_exog_from_season(dt_s_tup[1], len(endog))
  
          model = VAR(endog, exog)
          trend = dt_s_tup[0] if dt_s_tup[0] != "nc" else "n"
          results_per_deterministic_terms[dt_s_tup] = model.fit(
              maxlags=4, trend=trend, method="ols"
          )
      return results_per_deterministic_terms
  
imports: import numpy
  from numpy.testing import assert_, assert_allclose, assert_raises
  import statsmodels.datasets.macrodata.data
  from statsmodels.tsa.vector_ar.tests.JMulTi_results.parse_jmulti_vecm_output import sublists
  from statsmodels.tsa.vector_ar.var_model import VAR
  from .JMulTi_results.parse_jmulti_var_output import dt_s_tup_to_string, load_results_jmulti
label_desc: Use image node_id 4 for calling a global function with example usage: load_results_statsmodels(dataset) and returns: results_per_deterministic_terms