Tag Archives: exponential smoothing

ISF2017 presentation: Call centre forecasting using temporal aggregation

This is joint work with Devon K. Barrow and Bahman Rostami-Tabar and is an initial exploration of the benefits of using Multiple Temporal Aggregation, as implemented in MAPA for call centre forecasting. The preliminary results are encouraging. More details in the attached presentation. Abstract With thousands of call centres worldwide employing millions and serving billions… Read More: ISF2017 presentation: Call centre forecasting using temporal aggregation »

Multiple temporal aggregation: the story so far. Part III: MAPA

Multiple Aggregation Prediction Algorithm (MAPA) In this third post about modelling with Multiple Temporal Aggregation (MTA), I will explain how the Multiple Aggregation Prediction Algorithm (MAPA) works, which was the first incarnation of MTA for forecasting. MAPA is quite simple in its logic: a time series is temporally aggregated into multiple levels, at each level… Read More: Multiple temporal aggregation: the story so far. Part III: MAPA »

Multiple temporal aggregation: the story so far. Part II: The effects of TA

The effects of temporal aggregation In this post I will demonstrate the effects of temporal aggregation and motivate the use of multiple temporal aggregation (MTA). I will not delve into the econometric aspects of the discussion, but it is worthwhile to summarise key findings from the literature. A concise forecasting related summary is available in… Read More: Multiple temporal aggregation: the story so far. Part II: The… »

Multiple temporal aggregation: the story so far. Part I

Over the last years I have been working (with my co-authors!) on the idea of Multiple Temporal Aggregation (MTA) for time series forecasting. A number of papers have been published introducing and developing the idea further, or testing its effectiveness for forecasting. In this series of blog posts I will try to summarise the progress… Read More: Multiple temporal aggregation: the story so far. Part I »

MAPAx available for R & new MAPA package on CRAN

The previous version of the MAPA package implemented only the univariate aspect of the algorithm. Version 2.0.1 implements MAPAx as well, which allows incorporating regressors in your forecasts. In this paper we demonstrated the usefulness of temporal aggregation in the case of forecasting demand in the presence of promotions. In particular, we showed that MAPAx… Read More: MAPAx available for R & new MAPA package on CRAN »

ISIR 2016 research presentations

Last August I attended the International Symposium on Inventories, organised by the International Society for Inventory Research (ISIR 2016). This is the second time I had attended this conference and it has been again a very good experience. Interesting talks on a variety of relevant topics to forecasting research. I organised a special track on… Read More: ISIR 2016 research presentations »

Material for `Forecasting with R: A practical workshop”

Together with Fotios Petropoulos we gave a workshop on producing forecasts with R, at the International Symposium on Forecasting, 2016. You can find the material of the workshop here. The workshop notes assume knowledge of what the various forecasting methods do, which are only briefly explained in the workshop’s slides, and mostly focuses in showing… Read More: Material for `Forecasting with R: A practical workshop” »

A fundamental idea in extrapolative forecasting

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 »