Erratum regarding missing Declaration of Competing Interest statements in previously published articles (International Journal of Forecasting (2018) 34(4) (802–808), (S0169207018300785), (10.1016/j.ijforecast.2018.06.001));The M4 Competition: Results, findings, conclusion and way forward

International Journal of Forecasting

Volumn 34, Issue 4, 2018, Pages 802-808

  Makridakis, Spyros ^a,b   Spiliotis, Evangelos ^c   Assimakopoulos, Vassilios ^c  

^a UNIVERSITY OF NICOSIA   (Cyprus)

^b Institute For the Future (IFF)   (Cyprus)

^c NATIONAL TECHNICAL UNIVERSITY OF ATHENS   (Greece)

Author keywords

Benchmarking methods; Forecasting accuracy; Forecasting competitions; M Competitions; Machine Learning (ML) methods; Practice of forecasting; Prediction intervals (PIs); Time series methods

Indexed keywords

EID: 85048705073     PISSN: 01692070     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ijforecast.2021.01.013     Document Type: Erratum

References (12)

1. Ahmed, N.K., Atiya, A.F., Gayar, N.E., El-Shishiny, H., An empirical comparison of machine learning models for time series forecasting. Econometric Reviews 29:5–6 (2010), 594–621.
2. Hyndman, R., Athanasopoulos, G., Bergmeir, C., Caceres, G., Chhay, L., & O'Hara-Wild, M. et al., (2018). Forecast: Forecasting functions for time series and linear models. R package version 8.3.
3. Kang, Y., Hyndman, R.J., Smith-Miles, K., Visualising forecasting algorithm performance using time series instance spaces. International Journal of Forecasting 33:2 (2017), 345–358.
4. M4 Team (2018). M4 competitor's guide: prizes and rules. See https://www.m4.unic.ac.cy/wp-content/uploads/2018/03/M4-Competitors-Guide.pdf.
5. Makridakis, S., Andersen, A., Carbone, R., Fildes, R., Hibon, M., et al. The accuracy of extrapolation (time series) methods: results of a forecasting competition. Journal of Forecasting 1 (1982), 111–153.
6. Makridakis, S., Assimakopoulos, V., Spiliotis, E., Objectivity, reproducibility and replicability in forecasting research. International Journal of Forecasting, 34(3), 2018 (in press).
7. Makridakis, S., Chatfield, C., Hibon, M., Lawrence, M., Mills, T., et al. The M2-competition: A real-time judgmentally based forecasting study. International Journal of Forecasting 9:1 (1993), 5–22.
8. Makridakis, S., Hibon, M., Accuracy of forecasting: an empirical investigation. Journal of the Royal Statistical Society, Series A (General) 142:2 (1979), 97–145.
9. Makridakis, S., Hibon, M., The M3-Competition: results, conclusions and implications. International Journal of Forecasting 16:4 (2000), 451–476.
10. Makridakis, S., Spiliotis, E., Assimakopoulos, V., Statistical and machine learning forecasting methods: concerns and ways forward. PLOS ONE 13:3 (2018), 1–26.
11. Montero-Manso, P., Netto, C., & Talagala, T. (2018). M4comp2018: Data from the M4-Competition. R package version 0.1.0.
12. Petropoulos, F., Makridakis, S., Assimakopoulos, V., Nikolopoulos, K., ‘Horses for courses’ in demand forecasting. European Journal of Operational Research 237:1 (2014), 152–163.