code: def fit_austourists_with_R_params(model, results_R, set_state=False):
      """
      Fit the model with params as found by R's forecast package
      """
      params = get_params_from_R(results_R)
      with model.fix_params(dict(zip(model.param_names, params))):
          fit = model.fit(disp=False)
  
      if set_state:
          states_R = get_states_from_R(results_R, model._k_states)
          fit.states = states_R
      return fit
  
imports: from statsmodels.compat.pandas import QUARTER_END
  from statsmodels.compat.platform import PLATFORM_LINUX32, PLATFORM_WIN
  from itertools import product
  import json
  import pathlib
  import numpy
  from numpy.testing import assert_allclose, assert_almost_equal
  import pandas
  import pytest
  import scipy.stats
  from statsmodels.tsa.exponential_smoothing.ets import ETSModel
  import statsmodels.tsa.holtwinters
  import statsmodels.tsa.statespace.exponential_smoothing
label_desc: Use image node_id 12 for calling a global function with example usage: fit_austourists_with_R_params(model, results_R, set_state) and returns: fit