class_docstr: Results for forecasting using STL to remove seasonality
  
  Parameters
  ----------
  stl : STL
      The STL instance used to decompose the data.
  result : DecomposeResult
      The result of applying STL to the data.
  model : Model
      The time series model used to model the non-seasonal dynamics.
  model_result : Results
      Model results instance supporting, at a minimum, ``forecast``.
class_docstr_tok: ["Results","for","forecasting","using","STL","to","remove","seasonality","Parameters","--","--","--","--","--","stl",":","STL","The","STL","instance","used","to","decompose","the","data",".","result",":","DecomposeResult","The","result","of","applying","STL","to","the","data",".","model",":","Model","The","time","series","model","used","to","model","the","non-seasonal","dynamics",".","model_result",":","Results","Model","results","instance","supporting",",","at","a","minimum",",","``","forecast","``","."]
docstr: Summary of both the STL decomposition and the model fit.
  
  Returns
  -------
  Summary
      The summary of the model fit and the STL decomposition.
  
  Notes
  -----
  Requires that the model's result class supports ``summary`` and
  returns a ``Summary`` object.
docstr_tok: ["Summary","of","both","the","STL","decomposition","and","the","model","fit",".","Returns","--","--","--","-","Summary","The","summary","of","the","model","fit","and","the","STL","decomposition",".","Notes","--","--","-","Requires","that","the","model","'s","result","class","supports","``","summary","``","and","returns","a","``","Summary","``","object","."]
code: def summary(self) -> Summary:
      """
      Summary of both the STL decomposition and the model fit.
  
      Returns
      -------
      Summary
          The summary of the model fit and the STL decomposition.
  
      Notes
      -----
      Requires that the model's result class supports ``summary`` and
      returns a ``Summary`` object.
      """
      if not hasattr(self._model_result, "summary"):
          raise AttributeError(
              "The model result does not have a summary attribute."
          )
      summary: Summary = self._model_result.summary()
      if not isinstance(summary, Summary):
          raise TypeError(
              "The model result's summary is not a Summary object."
          )
      summary.tables[0].title = (
          "STL Decomposition and " + summary.tables[0].title
      )
      config = self._stl.config
      left_keys = ("period", "seasonal", "robust")
      left_data = []
      left_stubs = []
      right_data = []
      right_stubs = []
      for key in config:
          new = key.capitalize()
          new = new.replace("_", " ")
          if new in ("Trend", "Low Pass"):
              new += " Length"
          is_left = any(key.startswith(val) for val in left_keys)
          new += ":"
          stub = f"{new:<23s}"
          val = f"{str(config[key]):>13s}"
          if is_left:
              left_stubs.append(stub)
              left_data.append([val])
          else:
              right_stubs.append(" " * 6 + stub)
              right_data.append([val])
      tab = SimpleTable(
          left_data, stubs=tuple(left_stubs), title="STL Configuration"
      )
      tab.extend_right(SimpleTable(right_data, stubs=right_stubs))
      summary.tables.append(tab)
      return summary
  
imports: from statsmodels.compat.pandas import Substitution, is_int_index
  import datetime
  from typing import Any, Optional, Union
  import numpy
  import pandas
  from statsmodels.base.data import PandasData
  from statsmodels.iolib.summary import SimpleTable, Summary
  from statsmodels.tools.docstring import Docstring, Parameter, indent
  from statsmodels.tsa.base.prediction import PredictionResults
  from statsmodels.tsa.base.tsa_model import get_index_loc, get_prediction_index
  from statsmodels.tsa.seasonal import STL, DecomposeResult
  from statsmodels.tsa.statespace.kalman_filter import _check_dynamic
label_desc: Use image node_id 7 for calling the STLForecastResults obj's underlying member method code with example usage: obj.summary() and returns: summary