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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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Blog

  • smooth in python: Non-normal distributions in ETS/ARIMA
  • Hans Levenbach’s classification scheme for trend/seasonal components
  • smooth in python: multiple seasonal ETS
  • smooth in python: ETS with explanatory variables
  • smooth in python: ETS forecast combination

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ADAM AI and ML ARIMA bla-bla-bla CES changepoint combinations Competitions complex variables conferences consultancy EDA 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

  • Behavior-Driven Development in R Shiny: Modeling User Behavior with When Steps 2026-05-26
  • Speeding up Stan model builds for R package developers 2026-05-26
  • Repost: ctrlvee: Extract external R code and insert inline 2026-05-22
  • Functions over Idioms – Writing R in Python with rfuns 2026-05-22
  • [R] How to use ggpattern to add patterns to ggplot2 plots 2026-05-22

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Ivan Svetunkov
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