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: The result class from the estimated model
docstr_tok: ["The","result","class","from","the","estimated","model"]
code: def model_result(self) -> Any:
      """The result class from the estimated model"""
      return self._model_result
  
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 6 for calling the STLForecastResults obj's underlying member method code with example usage: obj.model_result() and returns: self