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M-competitions, from M4 to M5: reservations and expectations

2020-03-012024-03-15 3 Comments

UPDATE: I have also written a short post on “The role of M competitions in forecasting“, which gives historical perspective and a brief overview of the main findings of the previous competitions. Some of you might have noticed that the guidelines for the M5 competition have finally been released. Those of you who have previously […]

Naughty APEs and the quest for the holy grail

2017-07-292024-04-04 Leave a comment

Today I want to tell you a story of naughty APEs and the quest for the holy grail in forecasting. The topic has already been known for a while in academia, but is widely ignored by practitioners. APE stands for Absolute Percentage Error and is one of the simplest error measures, which is supposed to […]

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  • There’s no such thing as “deterministic forecast”
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  • Forecasting Competitions Datasets in Python
  • Risky business: how to select your model based on risk preferences

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ADAM AI and ML ARIMA bla-bla-bla CES changepoint combinations Competitions complex variables conferences consultancy English error measures estimators ETS extrapolation methods greybox GUM hierarchies history Information criteria intermittent demand ISF ISMS model combination model selection multivariate models papers personal PhD presentations programming Python R regression regular demand Seasonality SMA smooth statistics stories teaching theory time series uncertainty

Comments

  • Ivan Svetunkov on Intermittent demand classifications: is that what you need?
  • Kishor Kukreja on Intermittent demand classifications: is that what you need?
  • Ivan Svetunkov on Who is “Forecasting academia”?
  • Mohamed Merabtine on Who is “Forecasting academia”?
  • Ivan Svetunkov on Why Naive is not a good benchmark for intermittent demand

RSS RBloggers feed

  • Agentic coding with R workshop 2026-03-02
  • rOpenSci Dev Guide 1.0.0: Trilingual and Improved 2026-03-02
  • How to Fit Hierarchical Bayesian Models in R with brms: Partial Pooling Explained 2026-03-01
  • Declaring generative AI use in research and university studies 2026-03-01
  • My Presentation at Risk 2026: Lightweight Transfer Learning for Financial Forecasting 2026-03-01

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Ivan Svetunkov
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