class_docstr: Custom forecaster. todo: write docstring.
  
  todo: describe your custom forecaster here
  
  Parameters
  ----------
  parama : int
      descriptive explanation of parama
  paramb : string, optional (default='default')
      descriptive explanation of paramb
  paramc : boolean, optional (default= whether paramb is not the default)
      descriptive explanation of paramc
  and so on
  est : sktime.estimator, BaseEstimator descendant
      descriptive explanation of est
  est2: another estimator
      descriptive explanation of est2
  and so on
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docstr: Update time series to incremental training data.
  
  private _update containing the core logic, called from update
  
  State required:
      Requires state to be "fitted".
  
  Accesses in self:
      Fitted model attributes ending in "_"
      self.cutoff
  
  Writes to self:
      Sets fitted model attributes ending in "_", if update_params=True.
      Does not write to self if update_params=False.
  
  Parameters
  ----------
  y : sktime time series object
      guaranteed to be of an mtype in self.get_tag("y_inner_mtype")
      Time series with which to update the forecaster.
      if self.get_tag("scitype:y")=="univariate":
          guaranteed to have a single column/variable
      if self.get_tag("scitype:y")=="multivariate":
          guaranteed to have 2 or more columns
      if self.get_tag("scitype:y")=="both": no restrictions apply
  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
  update_params : bool, optional (default=True)
      whether model parameters should be updated
  
  Returns
  -------
  self : reference to self
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code: def _update(self, y, X=None, update_params=True):
      """Update time series to incremental training data.
  
      private _update containing the core logic, called from update
  
      State required:
          Requires state to be "fitted".
  
      Accesses in self:
          Fitted model attributes ending in "_"
          self.cutoff
  
      Writes to self:
          Sets fitted model attributes ending in "_", if update_params=True.
          Does not write to self if update_params=False.
  
      Parameters
      ----------
      y : sktime time series object
          guaranteed to be of an mtype in self.get_tag("y_inner_mtype")
          Time series with which to update the forecaster.
          if self.get_tag("scitype:y")=="univariate":
              guaranteed to have a single column/variable
          if self.get_tag("scitype:y")=="multivariate":
              guaranteed to have 2 or more columns
          if self.get_tag("scitype:y")=="both": no restrictions apply
      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
      update_params : bool, optional (default=True)
          whether model parameters should be updated
  
      Returns
      -------
      self : reference to self
      """
  
file_path: sktime/extension_templates/forecasting.py
imports: from sktime.forecasting.base import BaseForecaster
label_desc: Use image node_id 4 for calling the MyForecaster obj's underlying member method code with example usage: obj._update(y, X, update_params) without return types