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The future of forecasting competitions: Design attributes and principles
16 references·1 citing·43 second hop
The future of forecasting competitions: Design attributes and principles (2022)The future of forecasting competitions: D…Kaggle forecasting competitions: An overlooked learning opportunity (2020)Kaggle forecasting competitio…The M4 Competition: 100,000 time series and 61 forecasting methods (2019)The M4 Competition: 100,000 t…FFORMA: Feature-based forecast model averaging (2019)FFORMA: Feature-based forecas…A hybrid method of exponential smoothing and recurrent neural networks for time series forecasting (2019)A hybrid method of exponentia…What does research reproducibility mean? (2016)What does research reproducib…Optimal combination forecasts for hierarchical time series (2011)Optimal combination forecasts…Advances in forecasting with neural networks? Empirical evidence from the NN3 competition on time series prediction (2011)Advances in forecasting with …The tourism forecasting competition (2010)The tourism forecasting compe…Another look at measures of forecast accuracy (2006)Another look at measures of f…The M3-Competition: results, conclusions and implications (2000)The M3-Competition: results, …Out-of-sample tests of forecasting accuracy: an analysis and review (2000)Out-of-sample tests of foreca…HARKing: Hypothesizing After the Results are Known (1998)HARKing: Hypothesizing After …The M2-competition: A real-time judgmentally based forecasting study (1993)The M2-competition: A real-ti…The accuracy of extrapolation (time series) methods: Results of a forecasting competition (1982)The accuracy of extrapolation…Accuracy of Forecasting: An Empirical Investigation (1979)Accuracy of Forecasting: An E…Experience with Forecasting Univariate Time Series and the Combination of Forecasts (1974)Experience with Forecasting U…The M6 forecasting competition: Bridging the gap between forecasting and investment decisions (2024)The M6 forecasting competitio…The Structure of Scientific Revolutions (1963)Investigating Causal Relations by Econometric Models and Cross-spectral Methods (1969)On the psychology of prediction. (1973)ARMA Models and the Box-Jenkins Methodology (1997)Time series forecasts of international travel demand for Australia (2002)Forecasting and operational research: a review (2008)Error measures for generalizing about forecasting methods: Empirical comparisons (1992)Exponential smoothing: The state of the art—Part II (2006)A review and comparison of strategies for multi-step ahead time series forecasting based on the NN5 forecasting competition (2012)Forecasting: theory and practice (2022)Combining forecasts: A review and annotated bibliography (1989)25 years of time series forecasting (2006)Strong Inference (1964)The Methodology of Scientific Research Programmes (1978)Shall we Really do it Again? The Powerful Concept of Replication is Neglected in the Social Sciences (2009)Scientific Utopia (2012)P-curve: A key to the file-drawer. (2013)The Logic of Scientific Discovery (2013)The Combination of Forecasts (1969)Time Series Analysis: Forecasting and Control (1977)Exponential smoothing: The state of the art (1985)Combining forecasts: A review and annotated bibliography (1990)Forecasting methods and applications (1993)Policy: NIH plans to enhance reproducibility (2014)The Galaxy platform for accessible, reproducible and collaborative biomedical analyses: 2016 update (2016)A solution to minimum sample size for regressions (2020)CONSORT 2025 statement: updated guideline for reporting randomised trials (2025)CONSORT 2025 statement: updated guideline for reporting randomised trials (2025)Forecasting Sales by Exponentially Weighted Moving Averages (1960)Bayesian Forecasting (1976)Tests for Forecast Encompassing (1998)Deep neural networks, gradient-boosted trees, random forests: Statistical arbitrage on the S&P 500 (2016)A Dual-Stage Attention-Based Recurrent Neural Network for Time Series Prediction (2017)The forthcoming Artificial Intelligence (AI) revolution: Its impact on society and firms (2017)Statistical and Machine Learning forecasting methods: Concerns and ways forward (2018)N-BEATS: Neural basis expansion analysis for interpretable time series forecasting (2019)Deep Learning for Time Series Forecasting: Tutorial and Literature Survey (2022)M5 accuracy competition: Results, findings, and conclusions (2022)Time Series Analysis Forecasting and Control. (1971)Strictly Proper Scoring Rules, Prediction, and Estimation (2007)Forecast evaluation for data scientists: common pitfalls and best practices (2022)Automatic Time Series Forecasting: The forecast Package for R (2008)Recurrent Neural Networks for Time Series Forecasting: Current status and future directions (2020)
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References

  • 2006Another look at measures of forecast accuracy5,736 cited
  • 1998HARKing: Hypothesizing After the Results are Known1,988 cited
  • 2000The M3-Competition: results, conclusions and implications1,700 cited
  • 1982The accuracy of extrapolation (time series) methods: Results of a forecasting competition1,465 cited
  • 2016What does research reproducibility mean?1,291 cited
  • 2000Out-of-sample tests of forecasting accuracy: an analysis and review1,014 cited
  • 2019The M4 Competition: 100,000 time series and 61 forecasting methods990 cited
  • 1974Experience with Forecasting Univariate Time Series and the Combination of Forecasts849 cited
  • 2019A hybrid method of exponential smoothing and recurrent neural networks for time series forecasting766 cited
  • 1979Accuracy of Forecasting: An Empirical Investigation514 cited
  • 2011Optimal combination forecasts for hierarchical time series471 cited
  • 2019FFORMA: Feature-based forecast model averaging313 cited
  • 2010The tourism forecasting competition286 cited
  • 2011Advances in forecasting with neural networks? Empirical evidence from the NN3 competition on time series prediction272 cited
  • 2020Kaggle forecasting competitions: An overlooked learning opportunity

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266 cited
  • 1993The M2-competition: A real-time judgmentally based forecasting study264 cited
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    • 2024The M6 forecasting competition: Bridging the gap between forecasting and investment decisions31 cited