code: def forecast_result():
      """The forecast model results."""
      df = (
          DataLoader()
          .load_peyton_manning()
          .iloc[-365:]
          .reset_index(drop=True)
      )
      df["ts"] = pd.to_datetime(df["ts"])
      model = SimpleSilverkiteEstimator()
      model.fit(df)
      x_mat = model.model_dict["x_mat"]
      fit_df = model.predict(df)
      fit_df["y"] = df["y"]
      fut_df = (
          pd.DataFrame(
              {
                  "ts": pd.date_range(
                      df["ts"].max(), freq="D", periods=15
                  )
              }
          )
          .iloc[1:]
          .reset_index(drop=True)
      )
      predict_df = model.predict(fut_df)
      fut_x_mat = model.forecast_x_mat
      return {
          "df": df,
          "fit_df": fit_df,
          "x_mat": x_mat,
          "predict_df": predict_df,
          "fut_x_mat": fut_x_mat,
      }
  
file_path: greykite/greykite/tests/sklearn/uncertainty/test_quantile_regression_uncertainty_model.py
imports: import pandas
  import pytest
  from greykite.common import constants
  from greykite.common.data_loader import DataLoader
  from greykite.sklearn.estimator.simple_silverkite_estimator import SimpleSilverkiteEstimator
  from greykite.sklearn.uncertainty.exceptions import UncertaintyError
  from greykite.sklearn.uncertainty.quantile_regression_uncertainty_model import QuantileRegressionUncertaintyModel
label_desc: Use image node_id 1 for calling a global function with example usage: forecast_result() and returns: dict