code: def test_Croston_against_r_implementation(smoothing, fh, r_forecast):
      """Test Croston estimator against the R package implementing the same algorithm.
  
      Testing forecasted values estimated by the R package of the Croston's method
      against the Croston method in sktime.
      R code to generate the hardcoded value for fh=10:
      ('PBS_dataset.csv' contains the data from 'load_PBS_dataset()'):
  
          PBS_file <- read.csv(file = '/content/PBS_dataset.csv')[,c('Scripts')]
          y <- ts(PBS_file)
          demand=ts(y)
          forecast <- croston(y,h = 10)
      Output:
          0.8688921
      """  # noqa: E501
      y = load_PBS_dataset()
      forecaster = Croston(smoothing)
      forecaster.fit(y)
      y_pred = forecaster.predict(fh=fh)
      np.testing.assert_almost_equal(
          y_pred, np.full(len(fh), r_forecast), decimal=5
      )
  
imports: import numpy
  import pytest
  from sktime.datasets import load_PBS_dataset
  from sktime.forecasting.croston import Croston
label_desc: Use image node_id 1 for calling a global function with example usage: test_Croston_against_r_implementation(smoothing, fh, r_forecast) without return types