Skip to content
OpenForecast
  • Blog
  • Events
    • Future events
    • Past events
  • Training
    • Demand Forecasting Principles
  • Consulting
  • Packages
    • 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
  • Resources
    • ADAM
    • SBA
    • Intermittent demand
    • Forecast evaluation
  • About us

ISMS

Presentation at ISMS2018

2018-06-19 by Ivan Svetunkov

This year I participated the Informs Society for Marketing Science Conference in Philadelphia. I presented a research that I work on together with Victoria Grigorieva, Yana Salihova and Florian Dost. This is an ongoing research, and we are trying to capture the dynamics of ecosystems on the market of mobile devices in order to see, … Read more

Categories Conferences Tags ISMS, Marketing stuff, presentations Leave a comment

Events

  • Demand Forecasting Principles Training, October 2026 on 2026-10-05 14:00

Blog

  • Website redesign
  • ISF2026: PTS Taxonomy of Multiple Source of Error State Space Models for Demand Forecasting
  • stick function for the EDA in time series
  • smooth in python: Non-normal distributions in ETS/ARIMA
  • Hans Levenbach’s classification scheme for trend/seasonal components

Tags

ADAM AI and ML ARIMA CES changepoint combinations Competitions complex variables conferences consultancy EDA error measures estimators ETS extrapolation methods greybox GUM history Information criteria intermittent demand ISF Marketing stuff model combination model selection multivariate models MUSE opinion 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

  • More progress with Tabler for R 2026-08-15
  • Token Maxxing 2026-08-15
  • A Tiny Iroshizuku Ink Shop in R 2026-08-15
  • ‘Zero-Shot Probabilistic Stock Returns Forecasting with Pretrained RVFL Networks’ accepted at COPA 2026 (and to appear in the Proceedings of Machine Learning Research) 2026-08-15
  • [R] Environment Variables in R Shiny-Server Container: Problem and Solutions 2026-08-15
  • Русский
  • Terms of Service
  • Privacy Policy
  • About us
  • Contact us

OpenForecast Ltd is registered in England and Wales, 11391477.

© 2026 OpenForecast • Built with GeneratePress