class_docstr: Class to build a VAR model
      
class_docstr_tok: ["Class","to","build","a","VAR","model"]
docstr: Returns the 'unfit' SARIMAX model with the given dataset and the
  selected best parameters. This can be used to fit or refit the model.
docstr_tok: ["Returns","the","'unfit","'","SARIMAX","model","with","the","given","dataset","and","the","selected","best","parameters",".","This","can","be","used","to","fit","or","refit","the","model","."]
code: def get_best_model(self, data: pd.DataFrame):
      """
      Returns the 'unfit' SARIMAX model with the given dataset and the
      selected best parameters. This can be used to fit or refit the model.
      """
      bestmodel = VARMAX(
          data, order=(self.best_p, self.best_q), trend="c"
      )
      return bestmodel
  
imports: import pdb
  from typing import Optional
  import warnings
  import itertools
  import operator
  import copy
  import numpy
  import pandas
  from pandas.core.generic import NDFrame
  import dask
  import dask.dataframe
  import matplotlib.pyplot
  import seaborn
  from statsmodels.tsa.statespace.varmax import VARMAX
  from sklearn.model_selection import TimeSeriesSplit
  from ...utils import print_dynamic_rmse
  from ...models.ar_based.param_finder import find_lowest_pq
  from ..build_base import BuildBase
label_desc: Use image node_id 6 for calling the BuildVAR obj's underlying member method code with example usage: obj.get_best_model(data) and returns: bestmodel