class_docstr: Base class for interfacing StatsForecast.
docstr: Make predictions out of sample.
  
  Parameters
  ----------
  fh : array-like
      The forecasters horizon with the steps ahead to to predict.
      Default is
      one-step ahead forecast, i.e. np.array([1]).
  
  Returns
  -------
  y_pred : pandas.Series
  Returns series of predicted values.
code: def _predict_fixed_cutoff(
      self, fh, X=None, return_pred_int=False, alpha=DEFAULT_ALPHA
  ):
      """Make predictions out of sample.
  
      Parameters
      ----------
      fh : array-like
          The forecasters horizon with the steps ahead to to predict.
          Default is
          one-step ahead forecast, i.e. np.array([1]).
  
      Returns
      -------
      y_pred : pandas.Series
      Returns series of predicted values.
      """
      n_periods = int(fh.to_relative(self.cutoff)[-1])
      result = self._forecaster.predict(
          h=n_periods,
          X=X.values if X is not None else X,
      )
  
      fh_abs = fh.to_absolute(self.cutoff)
      fh_idx = fh.to_indexer(self.cutoff)
      mean = pd.Series(
          result["mean"].values[fh_idx], index=fh_abs.to_pandas()
      )
      if return_pred_int:
          pred_ints = []
          for a in alpha:
              result = self._forecaster.predict(
                  h=n_periods,
                  X=X.values if X is not None else X,
                  level=int(100 * a),
              )
              pred_int = result.drop("mean", axis=1).values
              pred_int = pd.DataFrame(
                  pred_int[fh_idx, :],
                  index=fh_abs.to_pandas(),
                  columns=["lower", "upper"],
              )
              pred_ints.append(pred_int)
          return mean, pred_ints
      else:
          return pd.Series(mean, index=fh_abs.to_pandas())
  
file_path: sktime/sktime/forecasting/base/adapters/_statsforecast.py
imports: import pandas
  from sktime.forecasting.base import BaseForecaster
  from sktime.forecasting.base._base import DEFAULT_ALPHA
label_desc: Use image node_id 6 for calling the _StatsForecastAdapter obj's underlying member method code with example usage: obj._predict_fixed_cutoff(fh, X, return_pred_int, alpha) and returns: mean,  pred_ints, pd