Tag Archives: temporal hierarchies

Invited talk at Amazon Web Services

I was recently invited to give a talk at AWS in Berlin. I presented the current work on temporal and cross-temporal hierarchical forecasting. My view is that there is a lot of potential for these approaches to augment existing forecasting processes with relative ease. Considering the wider forecasting problem, we do not forecast for the… Read More »

ISF2019 talk: Cross-temporal coherent forecasts for tourism forecasting

This year’s International Symposium on Forecasting has been a great success. Very exciting talks and large attendance from both academics and practitioners. I really enjoy conferences that the two groups interact organically: only this way research is both relevant and adopted fast, so that it makes a difference! This year I was invited by Haiyan… Read More »

Towards the “one-number forecast”

1. Introductory remarks One of the recurrent topics in online discussions on sales forecasting and demand planning is the idea of the “one-number forecast”, that is a common view of the future on which multiple plans and decisions can be made, from different functions of an organisation. In principle, this is yet another idea around… Read More »

New R package nnfor: time series forecasting with neural networks

My new R package nnfor is available on CRAN. This collects the various neural network functions that appeared in TStools. See this post for demo of these functions. In summary the package includes: Automatic, semi-automatic or fully manual specification of MLP neural networks for time series modelling, that helps in specifying inputs with lags of the… Read More »

OR59 Keynote: Uncertainty in predictive modelling

I recently presented at the OR59 conference my views and current work (with colleagues) on uncertainty in predictive modelling. I think this is a topic that deserves quite a bit of research attention, as it has substnatial implications for estimation, model selection and eventually decision making. The talk has three parts: Argue (as others before… Read More »

Multiple temporal aggregation: the story so far. Part IV: Temporal Hierarchies

Temporal Hierarchies In the previous post we saw how the Multiple Aggregation Prediction Algortihm (MAPA) implements the ideas of MTA. We also saw that it has some limitations, particularly requiring splitting forecasts into subcomponents (level, trend and seasonality). Although some forecasting methods provide such outputs naturally, for example Exponential Smoothing and Theta, others do not.… Read More »

ISF 2017 presentation: A hierarchical approach to forecasting Scandinavian unemployment

This is joint work with Rickard Sandberg and looks at the implicit connections enforced by hierarchical time series forecasting, between the nodes of the hierarchy, contrasting them to VAR models that captures connections explicitly. Abstract The four major Scandinavian economies (Denmark, Finland, Sweden and Norway) have high workforce mobility and depending on market dynamics the… 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 »