mlsanityData to 7 Oct 2026

Forecasting: theory and practice

arXiv 2012.03854 ↗First posted 4 Dec 2020stat.AP cs.LG econ.EMcited by 36

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Abstract (arXiv)

Forecasting has always been at the forefront of decision making and planning. The uncertainty that surrounds the future is both exciting and challenging, with individuals and organisations seeking to minimise risks and maximise utilities. The large number of forecasting applications calls for a diverse set of forecasting methods to tackle real-life challenges. This article provides a non-systematic review of the theory and the practice of forecasting. We provide an overview of a wide range of theoretical, state-of-the-art models, methods, principles, and approaches to prepare, produce, organise, and evaluate forecasts. We then demonstrate how such theoretical concepts are applied in a variety of real-life contexts. We do not claim that this review is an exhaustive list of methods and applications. However, we wish that our encyclopedic presentation will offer a point of reference for the rich work that has been undertaken over the last decades, with some key insights for the future of forecasting theory and practice. Given its encyclopedic nature, the intended mode of reading is non-linear. We offer cross-references to allow the readers to navigate through the various topics. We complement the theoretical concepts and applications covered by large lists of free or open-source software implementations and publicly-available databases.

Key facts. Cited by 36 papers in the map (data through 7 Oct 2026). First posted on arXiv 4 Dec 2020.

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Citing papers per year: 2021: 2; 2022: 11; 2023: 9; 2024: 8; 2025: 6.

36 papers.

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  1. 2022Forecast Evaluation for Data Scientists: Common Pitfalls and Best Practicescited by 54
  2. 2022Forecast combinations: an over 50-year reviewcited by 34
  3. 2022Distributional neural networks for electricity price forecastingcited by 24
  4. 2023Generative learning for nonlinear dynamicscited by 22
  5. 2022Review of automated time series forecasting pipelinescited by 17
  6. 2022Epicasting: An Ensemble Wavelet Neural Network (EWNet) for Forecasting Epidemicscited by 16
  7. 2022A review of machine learning concepts and methods for addressing challenges in probabilistic hydrological post-processing and forecastingcited by 12
  8. 2022W-Transformers : A Wavelet-based Transformer Framework for Univariate Time Series Forecastingcited by 12
  9. 2023Counterfactual Explanations for Time Series Forecastingcited by 10
  10. 2025Deep Learning for Time Series Forecasting: A Surveycited by 10
  11. 2023A feature selection method based on Shapley values robust to concept shift in regressioncited by 6
  12. 2022Aggregating distribution forecasts from deep ensemblescited by 5
24 more
  1. 2023Brain-Inspired Spiking Neural Network for Online Unsupervised Time Series Predictioncited by 5
  2. 2023A Joint Time-frequency Domain Transformer for Multivariate Time Series Forecastingcited by 5
  3. 2021Privacy-preserving Federated Learning for Residential Short Term Load Forecastingcited by 4
  4. 2024Using dynamic loss weighting to boost improvements in forecast stabilitycited by 4
  5. 2021Expert Aggregation for Financial Forecastingcited by 3
  6. 2025On the retraining frequency of global models in retail demand forecastingcited by 3
  7. 2025Leveraging Asynchronous Cross-border Market Data for Improved Day-Ahead Electricity Price Forecasting in European Marketscited by 3
  8. 2023A Natural Gas Consumption Forecasting System for Continual Learning Scenarios based on Hoeffding Trees with Change Point Detection Mechanismcited by 2
  9. 2023Sparse Transformer with Local and Seasonal Adaptation for Multivariate Time Series Forecastingcited by 2
  10. 2024Efficient mid-term forecasting of hourly electricity load using generalized additive modelscited by 2
  11. 2024Stratify: Unifying Multi-Step Forecasting Strategiescited by 2
  12. 2025A Hybrid Strategy for Probabilistic Forecasting and Trading of Aggregated Wind-Solar Power: Design and Analysis in HEFTCom2024cited by 2
  13. 2025Explainable time-series forecasting with sampling-free SHAP for Transformerscited by 2
  14. 2022A Hybrid Framework for Sequential Data Prediction with End-to-End Optimizationcited by 1
  15. 2023Hierarchical forecasting for aggregated curves with an application to day-ahead electricity price auctionscited by 1
  16. 2023Improving the forecast accuracy of wind power by leveraging multiple hierarchical structurecited by 1
  17. 2024GeOT: A spatially explicit framework for evaluating spatio-temporal predictionscited by 1
  18. 2024Time-Series Forecasting in Smart Manufacturing Systems: An Experimental Evaluation of the State-of-the-art Algorithmscited by 1
  19. 2022fETSmcs: Feature-based ETS model component selectioncited by 0
  20. 2022Knowledge-based Deep Learning for Modeling Chaotic Systemscited by 0
  21. 2024Efficient State Space Model via Fast Tensor Convolution and Block Diagonalizationcited by 0
  22. 2024Time Series Analysis in Compressor-Based Machines: A Surveycited by 0
  23. 2024Using ARIMA to Predict the Expansion of Subscriber Data Consumptioncited by 0
  24. 2025AquaCast: Urban Water Dynamics Forecasting with Precipitation-Informed Multi-Input Transformercited by 0