code: def forecast_ces(obj, h, level=None):
      fcst = pegelsfcast_C(h, obj)
      out = {"mean": fcst}
      out["fitted"] = obj["fitted"]
      if level is not None:
          pi = _simulate_pred_intervals(model=obj, h=h, level=level)
          out = {**out, **pi}
      return out
  
imports: import math
  from typing import Tuple
  import numpy
  from numba import njit
  from statsmodels.tsa.seasonal import seasonal_decompose
  from .ets import restrict_to_bounds, results
  from .utils import CACHE, NOGIL
label_desc: Use image node_id 15 for calling a global function with example usage: forecast_ces(obj, h, level) and returns: out