class_docstr: Base class for interfacing tbats forecasting algorithms.
class_docstr_tok: ["Base","class","for","interfacing","tbats","forecasting","algorithms","."]
code: def _instantiate_model(self):
      n_jobs = check_n_jobs(self.n_jobs)
      sp = check_sp(self.sp, enforce_list=True)
  
      return self._ModelClass(
          use_box_cox=self.use_box_cox,
          box_cox_bounds=self.box_cox_bounds,
          use_trend=self.use_trend,
          use_damped_trend=self.use_damped_trend,
          seasonal_periods=sp,
          use_arma_errors=self.use_arma_errors,
          show_warnings=self.show_warnings,
          n_jobs=n_jobs,
          multiprocessing_start_method=self.multiprocessing_start_method,
          context=self.context,
      )
  
file_path: sktime/sktime/forecasting/base/adapters/_tbats.py
imports: import numpy
  import pandas
  from sktime.forecasting.base import BaseForecaster
  from sktime.utils.validation import check_n_jobs
  from sktime.utils.validation.forecasting import check_sp
label_desc: Use image node_id 3 for calling the _TbatsAdapter obj's underlying member method code with example usage: obj._instantiate_model() and returns: self