class_docstr: Base parameter fitting estimator class.
  
  The base parameter fitter specifies the methods and method signatures that all
  parameter fitter have to implement.
  
  Specific implementations of these methods is deferred to concrete instances.
docstr: Fit estimator and estimate parameters.
  
  State change:
      Changes state to "fitted".
  
  Writes to self:
      Sets self._is_fitted flag to True.
      Writes `X` to self._X.
      Sets fitted model attributes ending in "_".
  
  Parameters
  ----------
  X : time series in sktime compatible data container format
          Time series to which to fit the forecaster in the update.
      y can be in one of the following formats, must be same scitype as in fit:
      Series scitype: pd.Series, pd.DataFrame, or np.ndarray (1D or 2D)
      Panel scitype: pd.DataFrame with 2-level row MultiIndex,
          3D np.ndarray, list of Series pd.DataFrame, or nested pd.DataFrame
      Hierarchical scitype: pd.DataFrame with 3 or more level row MultiIndex
      For further details:
          on usage, see forecasting tutorial examples/01_forecasting.ipynb
          on specification of formats, examples/AA_datatypes_and_datasets.ipynb
  
  Returns
  -------
  self : Reference to self.
docstr_tok: ["Fit","estimator","and","estimate","parameters",".","State","change",":","Changes","state","to","``","fitted","''",".","Writes","to","self",":","Sets","self._is_fitted","flag","to","True",".","Writes","`","X","`","to","self._X",".","Sets","fitted","model","attributes","ending","in","``","_","''",".","Parameters","--","--","--","--","--","X",":","time","series","in","sktime","compatible","data","container","format","Time","series","to","which","to","fit","the","forecaster","in","the","update",".","y","can","be","in","one","of","the","following","formats",",","must","be","same","scitype","as","in","fit",":","Series","scitype",":","pd.Series",",","pd.DataFrame",",","or","np.ndarray","(","1D","or","2D",")","Panel","scitype",":","pd.DataFrame","with","2-level","row","MultiIndex",",","3D","np.ndarray",",","list","of","Series","pd.DataFrame",",","or","nested","pd.DataFrame","Hierarchical","scitype",":","pd.DataFrame","with","3","or","more","level","row","MultiIndex","For","further","details",":","on","usage",",","see","forecasting","tutorial","examples\/01_forecasting.ipynb","on","specification","of","formats",",","examples\/AA_datatypes_and_datasets.ipynb","Returns","--","--","--","-","self",":","Reference","to","self","."]
code: def fit(self, X):
      """Fit estimator and estimate parameters.
  
      State change:
          Changes state to "fitted".
  
      Writes to self:
          Sets self._is_fitted flag to True.
          Writes `X` to self._X.
          Sets fitted model attributes ending in "_".
  
      Parameters
      ----------
      X : time series in sktime compatible data container format
              Time series to which to fit the forecaster in the update.
          y can be in one of the following formats, must be same scitype as in fit:
          Series scitype: pd.Series, pd.DataFrame, or np.ndarray (1D or 2D)
          Panel scitype: pd.DataFrame with 2-level row MultiIndex,
              3D np.ndarray, list of Series pd.DataFrame, or nested pd.DataFrame
          Hierarchical scitype: pd.DataFrame with 3 or more level row MultiIndex
          For further details:
              on usage, see forecasting tutorial examples/01_forecasting.ipynb
              on specification of formats, examples/AA_datatypes_and_datasets.ipynb
  
      Returns
      -------
      self : Reference to self.
      """
      # check X is not None
      assert X is not None, "X cannot be None, but found None"
  
      # if fit is called, estimator is reset, including fitted state
      self.reset()
  
      # check and convert X/y
      X_inner = self._check_X(X=X)
  
      # set internal X to the new X
      self._update_X(X_inner)
  
      # checks and conversions complete, pass to inner fit
      #####################################################
      self._fit(X=X_inner)
  
      # this should happen last
      self._is_fitted = True
  
      return self
  
file_path: sktime/sktime/param_est/base.py
imports: from sktime.base import BaseEstimator
  from sktime.datatypes import VectorizedDF, check_is_scitype, convert, scitype_to_mtype, update_data
  from sktime.utils.sklearn import is_sklearn_transformer
  from sktime.utils.validation._dependencies import _check_estimator_deps
  from sktime.utils.warnings import warn
label_desc: Use image node_id 3 for calling the BaseParamFitter obj's underlying member method code with example usage: obj.fit(X) and returns: self