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ETS experiments

Main results

dataset metric ets_statsforecast ets_r ets_statsmodels[1]
Hourly MASE 1.61 1.82 21848.5
Hourly time 18.79 35.45 112.35
Daily MASE 3.23 3.25 325.42
Daily time 26.24 17.78 19.97
Weekly MASE 2.55 2.53 2.68
Weekly time 1.78 2.12 1.56
Monthly MASE 0.97 0.95 3.75016e+07
Monthly time 512.7 907.23 2285.11
Quarterly MASE 1.17 1.16 9.01169e+07
Quarterly time 88.48 75.78 280.89
Yearly MASE 3.09 3.44 101.64
Yearly time 6.73 15.38 34.35
[1] The model ETSModel from statsmodels had performance problems for particular series. An issue was opened and answered.

Reproducibility

To reproduce the main results you have:

  1. Execute conda env create -f environment.yml.
  2. Activate the environment using conda activate ets.
  3. Run the experiments using python -m src.[model] --dataset M4 --group [group] where [model] can be statsforecast, and [group] can be Daily, Hourly and Weekly.
  4. To run R experiments you have to prepare the data using python -m src.data --dataset M4 --group [group] for each [group]. Once it is done, just run Rscript src/ets_r.R [group].
  5. Finally you can evaluate the forecasts using python -m src.evaluation.