class_docstr: Base adapter class for StatsForecast models.
class_docstr_tok: ["Base","adapter","class","for","StatsForecast","models","."]
docstr: Forecast time series at future horizon.
  
  private _predict containing the core logic, called from predict
  
  State required:
      Requires state to be "fitted".
  
  Accesses in self:
      Fitted model attributes ending in "_"
      self.cutoff
  
  Parameters
  ----------
  fh : guaranteed to be ForecastingHorizon or None, optional (default=None)
      The forecasting horizon with the steps ahead to to predict.
      If not passed in _fit, guaranteed to be passed here
  X : sktime time series object, optional (default=None)
      guaranteed to be of an mtype in self.get_tag("X_inner_mtype")
      Exogeneous time series for the forecast
  
  Returns
  -------
  y_pred : sktime time series object
      should be of the same type as seen in _fit, as in "y_inner_mtype" tag
      Point predictions
docstr_tok: ["Forecast","time","series","at","future","horizon",".","private","_predict","containing","the","core","logic",",","called","from","predict","State","required",":","Requires","state","to","be","``","fitted","''",".","Accesses","in","self",":","Fitted","model","attributes","ending","in","``","_","''","self.cutoff","Parameters","--","--","--","--","--","fh",":","guaranteed","to","be","ForecastingHorizon","or","None",",","optional","(","default=None",")","The","forecasting","horizon","with","the","steps","ahead","to","to","predict",".","If","not","passed","in","_fit",",","guaranteed","to","be","passed","here","X",":","sktime","time","series","object",",","optional","(","default=None",")","guaranteed","to","be","of","an","mtype","in","self.get_tag","(","``","X_inner_mtype","''",")","Exogeneous","time","series","for","the","forecast","Returns","--","--","--","-","y_pred",":","sktime","time","series","object","should","be","of","the","same","type","as","seen","in","_fit",",","as","in","``","y_inner_mtype","''","tag","Point","predictions"]
code: def _predict(self, fh, X):
      """Forecast time series at future horizon.
  
      private _predict containing the core logic, called from predict
  
      State required:
          Requires state to be "fitted".
  
      Accesses in self:
          Fitted model attributes ending in "_"
          self.cutoff
  
      Parameters
      ----------
      fh : guaranteed to be ForecastingHorizon or None, optional (default=None)
          The forecasting horizon with the steps ahead to to predict.
          If not passed in _fit, guaranteed to be passed here
      X : sktime time series object, optional (default=None)
          guaranteed to be of an mtype in self.get_tag("X_inner_mtype")
          Exogeneous time series for the forecast
  
      Returns
      -------
      y_pred : sktime time series object
          should be of the same type as seen in _fit, as in "y_inner_mtype" tag
          Point predictions
      """
      X_predict_input = X.to_numpy(copy=False) if X is not None else X
  
      in_sample_horizon, out_of_sample_horizon = self._split_horizon(fh)
  
      point_predictions = []
  
      if in_sample_horizon:
          in_sample_point_predictions = (
              self._predict_in_or_out_of_sample(
                  in_sample_horizon, "in-sample"
              )
          )
          point_predictions.append(in_sample_point_predictions)
  
      if out_of_sample_horizon:
          out_of_sample_point_predictions = (
              self._predict_in_or_out_of_sample(
                  out_of_sample_horizon,
                  "out-of-sample",
                  X=X_predict_input,
              )
          )
          point_predictions.append(out_of_sample_point_predictions)
  
      final_point_predictions = pandas.concat(
          point_predictions, copy=False
      )
      final_point_predictions.name = self._y.name
  
      return final_point_predictions
  
imports: from inspect import signature
  from typing import Dict
  from warnings import warn
  import pandas
  from sktime.forecasting.base import BaseForecaster
label_desc: Use image node_id 11 for calling the _GeneralisedStatsForecastAdapter obj's underlying member method code with example usage: obj._predict(fh, X) and returns: final_point_predictions