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Commentary on the M5 forecasting competition

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  • Kolassa, Stephan

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  • Kolassa, Stephan, 2022. "Commentary on the M5 forecasting competition," International Journal of Forecasting, Elsevier, vol. 38(4), pages 1562-1568.
    • Handle: RePEc:eee:intfor:v:38:y:2022:i:4:p:1562-1568
    DOI: 10.1016/j.ijforecast.2021.08.006
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    References listed on IDEAS

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    1. Zeileis, Achim & Kleiber, Christian & Jackman, Simon, 2008. "Regression Models for Count Data in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 27(i08).
    2. Syntetos, Aris A. & Nikolopoulos, Konstantinos & Boylan, John E., 2010. "Judging the judges through accuracy-implication metrics: The case of inventory forecasting," International Journal of Forecasting, Elsevier, vol. 26(1), pages 134-143, January.
    3. Fildes, Robert & Kolassa, Stephan & Ma, Shaohui, 2022. "Post-script—Retail forecasting: Research and practice," International Journal of Forecasting, Elsevier, vol. 38(4), pages 1319-1324.
    4. Ulrich, Matthias & Jahnke, Hermann & Langrock, Roland & Pesch, Robert & Senge, Robin, 2021. "Distributional regression for demand forecasting in e-grocery," European Journal of Operational Research, Elsevier, vol. 294(3), pages 831-842.
    5. Fildes, Robert & Ma, Shaohui & Kolassa, Stephan, 2022. "Retail forecasting: Research and practice," International Journal of Forecasting, Elsevier, vol. 38(4), pages 1283-1318.
    6. Andrew Prahl & Lyn Van Swol, 2017. "Understanding algorithm aversion: When is advice from automation discounted?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 36(6), pages 691-702, September.
    7. Evgeny A. Antipov & Elena B. Pokryshevskaya, 2020. "Interpretable machine learning for demand modeling with high-dimensional data using Gradient Boosting Machines and Shapley values," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 19(5), pages 355-364, October.
    8. Phillip Yelland & Zeynep Erkin Baz & David Serafini, 2019. "Forecasting at Scale: The Architecture of a Modern Retail Forecasting System," Foresight: The International Journal of Applied Forecasting, International Institute of Forecasters, issue 55, pages 10-18, Fall.
    9. Mohammadipour, Maryam & Boylan, John E., 2012. "Forecast horizon aggregation in integer autoregressive moving average (INARMA) models," Omega, Elsevier, vol. 40(6), pages 703-712.
    10. Kolassa, Stephan, 2016. "Evaluating predictive count data distributions in retail sales forecasting," International Journal of Forecasting, Elsevier, vol. 32(3), pages 788-803.
    11. Ma, Shaohui & Fildes, Robert, 2022. "The performance of the global bottom-up approach in the M5 accuracy competition: A robustness check," International Journal of Forecasting, Elsevier, vol. 38(4), pages 1492-1499.
    12. Stephan Kolassa, 2016. "Commentary: That Feeling for Randomness," Foresight: The International Journal of Applied Forecasting, International Institute of Forecasters, issue 42, pages 44-47, Summer.
    13. Alireza Pooya & Morteza Pakdaman & Lotfi Tadj, 2019. "Exact and approximate solution for optimal inventory control of two-stock with reworking and forecasting of demand," Operational Research, Springer, vol. 19(2), pages 333-346, June.
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    Cited by:

    1. Fildes, Robert & Kolassa, Stephan & Ma, Shaohui, 2022. "Post-script—Retail forecasting: Research and practice," International Journal of Forecasting, Elsevier, vol. 38(4), pages 1319-1324.

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