code: def _naive(
      y: np.ndarray,  # time series
      h: int,  # forecasting horizon
      fitted: bool,  # fitted values
  ) -> Dict[str, np.ndarray]:
      fcst = {"mean": _repeat_val(val=y[-1], h=h)}
      if fitted:
          fitted_vals = np.full(y.size, np.nan, np.float32)
          fitted_vals[1:] = np.roll(y, 1)[1:]
          fcst["fitted"] = fitted_vals
      return fcst
  
file_path: statsforecast/statsforecast/utils.py
imports: from typing import Dict
  import math
  import os
  import warnings
  import numpy
  import pandas
  from scipy.stats import norm
  from utilsforecast.compat import DataFrame
  from utilsforecast.data import generate_series
label_desc: Use image node_id 5 for calling a global function with example usage: _naive(y, h, fitted) and returns: fcst