Tag Archives: exponential smoothing

ISF2017 presentation: DIY forecasting – judgement, models & judgmental model selection

This is joint work with Fotios Petropoulos and Kostantinos Nikolopoulos and discusses the performance of experts selecting forecasting models, against automatic statistical model selection, as well as providing guidelines how to maximise the benefits. This is very exciting research, demonstrating the both some limitations of statistical model selection (and avenues for new research), as well… Read More »

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 »

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 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 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 »

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 »

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 »