Fotios Petropoulos and I will be giving a workshop on how to produce forecasts using R. The focus will be on business forecasting applications and the workshop is part of the workshop series that runs as part of the 36th International Symposium on Forecasting on the 19th of June 2016. This workshop will provide a… Read More: Workshop on `Forecasting with R’ »
Extrapolative forecasting, using models such as exponential smoothing, is arguably not very complicated from a mathematical point of view, but it requires a shift in logic in terms of what is a good forecast. For this discussion I will use a simple form of exponential smoothing to demontrate my point. 1. The forecasting model: single… Read More: A fundamental idea in extrapolative forecasting »
D. Barrow and N. Kourentzes, 2016, International Journal of Production Economics, 177: 24-33. http://dx.doi.org/10.1016/j.ijpe.2016.03.017
I was looking for an intuitive way to demonstrate to my students the need for parsimony in model building, as well as the problem of overfitting and I remembered the humorous paper by James Wel: showing that elephants are obviously created by Fourier sine series! I went a step further and implemented some popular selection… Read More: How to fit an elephant? »
I will be hosting a special session on Estimating Demand Uncertainty in the upcoming International Society for Inventory Research conference ISIR2016. The link between forecasting and inventory calculations is often not as clear as it should be. This is evident by the formulas used for the safety stock calculation: the expected demand and its uncertainty… Read More: ISIR 2016: Special session on `Estimating Demand Uncertainty’ »
There is a new forecasting competition announced, the International Time Series Forecasting Competition “Computational Intelligence in Forecasting” CIF 2016. The competition is organised by Martin Stepnicka and Michal Burda within IEEE WCCI 2016 congress and it is related to a special session IJCNN-13 Advances in Computational Intelligence for Applied Time Series Forecasting (ACIATSF). For more… Read More: Forecasting competition: Computational Intelligence in Forecasting »
Lancaster Centre for Forecasting and Cardiff Business School, in collaboration with the IIF and SAS, are hosting a workshop on “Supply Chain Forecasting for Operations” on 28 and 29 June 2016 at Lancaster University, UK. The workshop is intended to stimulate forecasting research in the area of supply chain operations and selected papers will be… Read More: IIF Workshop on Supply Chain Forecasting for Operations »
Another interactive demo I created for the courses I teach. This one is about simple exponential smoothing and the main objective is to show the interaction between smoothing parameter and initial level in the fitting and holdout samples. A different interactive demo about exponential smoothing can be found here. A couple of points that may… Read More: Interactive simple exponential smoothing »
I made this little interactive demo for basic time series exploration and decomposition for my students. I uploaded it here in case someone else finds it useful. Some things to try: How does the seasonal plot looks like for seasonal and non-seasonal time series? How does the seasonal plot looks when the trend is not… Read More: RShiny demo for basic time series exploration »
Version 1.8 of tsintermittent has been submitted to CRAN and should be shortly available for download. Amongst various new checks on inputs to better accommodate handling multiple time series with data frames, a new option has been added to data.frc. When method=”auto” two things will happen: Function idclass(…,type=”PKa”) will be called to classify the time… Read More: Another update for tsintermittent »