Open Forecasting

Menu

Skip to content
  • Home
  • Events
    • Future events
    • Past events
  • smooth
    • smooth Github
    • smooth in Python
      • smooth functions
    • smooth in R
      • About adam() function
      • About es() function
      • Common parameters
      • smooth methods in R
  • greybox
    • greybox Github
    • greybox in Python
      • greybox on PyPI
    • greybox in R
  • Theory
    • Forecast evaluation
  • ADAM
  • SBA
  • About
  • Русский

changepoint

Online Detection of Forecast Model Inadequacies Using Forecast Errors

2025-06-112025-06-11 Leave a comment
Figure 6 from the paper, showing the proportion of GRP A&E admissions, the forecast errors and two detectors.

There’s a large and fascinating area in time series analysis called “changepoint detection”. I hadn’t worked in this area before, but thanks to Rebecca Killick and Thomas Grundy, I contributed to the paper “Online Detection of Forecast Model Inadequacies Using Forecast Errors“, which has just been published in the Journal of Time Series Analysis. DISCLAIMER: […]

  • Русский

Events

  • No events planned at the moment

Blog

  • smooth in python: ETS with explanatory variables
  • smooth in python: ETS forecast combination
  • smooth in python: ETS with model selection
  • smooth forecasting with the smooth package in Python
  • The real Dunning-Kruger effect

Tags

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

  • JAGS 5.0.0-beta is available 2026-05-04
  • Comparing R’s {targets} and dbt for Data Engineering 2026-05-04
  • The Magic of In-Context Learning (ICL): When Your Model Already Knows Your Data 2026-05-03
  • Bad Weather and the Subway 2026-05-02
  • You Don’t Need to Learn All the Weights on tabular data: The Case for rvflnet (a nonlinear expressive glmnet) on regression, classification and survival analysis 2026-05-02

Categories

Blog Authors

Ivan Svetunkov
  • Home
  • Future events
  • Past events
  • Using R
  • About
Рейтинг@Mail.ru