def METHOD_NAME(self, X, y=None, update_params=True):
    """Update wrapped transformer with X, optionally y.
    State required:
        Requires state to be "fitted".
    Writes to self:
        May update fitted model attributes ending in for the delegated
        transformer "_" via update.
    Parameters
    ----------
    X : Series or Panel, any supported mtype
        Data to fit transform to, of python type as follows:
            Series: pd.Series, pd.DataFrame, or np.ndarray (1D or 2D)
            Panel: pd.DataFrame with 2-level MultiIndex, list of pd.DataFrame,
                nested pd.DataFrame, or pd.DataFrame in long/wide format
    y : Series or Panel, default=None
        Additional data, e.g., labels for transformation
    update_params : bool, default=True
        whether the model is updated. Yes if true, if false, simply skips call.
        argument exists for compatibility with forecasting module.
    Returns
    -------
    self : a fitted instance of the estimator
    """
    estimator = self._get_delegate()
    estimator.update(y=y, X=X, update_params=update_params)
    return self