code: def _fit(
      self,
      series: TimeSeries,
      future_covariates: Optional[TimeSeries] = None,
  ):
      super()._fit(series, future_covariates)
  
      self._assert_univariate(series)
  
      # storing to restore the statsmodels model results object
      self.training_historic_future_covariates = future_covariates
  
      m = staARIMA(
          series.values(copy=False),
          exog=future_covariates.values(copy=False)
          if future_covariates
          else None,
          order=self.order,
          seasonal_order=self.seasonal_order,
          trend=self.trend,
      )
      self.model = m.fit()
  
      return self
  
file_path: darts/darts/models/forecasting/arima.py
imports: from typing import Optional, Tuple
  import numpy
  from statsmodels import __version_tuple__
  from statsmodels.tsa.arima.model import ARIMA
  from darts.logging import get_logger
  from darts.models.forecasting.forecasting_model import TransferableFutureCovariatesLocalForecastingModel
  from darts.timeseries import TimeSeries
label_desc: Use image node_id 3 for calling the ARIMA obj's underlying member method code with example usage: obj._fit(series, future_covariates) and returns: self