I am organising a special session on the upcoming International Symposium on Forecasting with the topic “Forecasting with Combinations and Hierarchies”. Please contact me if you are interested to contribute to this session. In many applications there are time series that can be hierarchically organised and can be grouped or aggregated in several ways, based… Read More »
Juan R. Trapero and I are organising a special session on Energy Forecasting within the Forecasting & Time Series Prediction stream at EURO2014. Energy modelling and forecasting has become essential to optimize the generation, control and distribution processes of countries’ energy systems. This special session calls for abstracts analyzing concepts, models, methodologies, case studies that… Read More »
In this post I introduce a new bias metric that has several desirable properties over traditional ones. When evaluating forecasting performance it is important to look at two elements: forecasting accuracy and bias. Although there has been substantial progress in the measurement of accuracy with various metrics being proposed, there has been rather limited progress… Read More »
N. Kourentzes, J. R. Trapero and I. Svetunkov, 2014.
Aris Syntetos, Mohamed Zied Babai, John Boylan, Stephan Kolassa and Kostas Nikolopoulos have prepared a questionnaire about supply chain forecasting to help them on their research for a review article on the topic. I think that surveying the community to identify important areas for academics and practitioners is commendable. You can participate by submitting your… Read More »
I recently became aware of a new forecasting competition: “International Forecasting Competition – Computational Intelligence in Forecasting”. The competition involves forecasting 91 time series of annual, quarterly, monthly and daily sampling frequency of various lengths. Although the competition is focused on computational intelligence methods (incl. fuzzy method, artificial neural networks, evolutionary algorithms, decision & regression… Read More »
Seasonality is a common characteristic of time series. It can appear in two forms: additive and multiplicative. In the former case the amplitude of the seasonal variation is independent of the level, whereas in the latter it is connected. The following figure highlights this: Note that in the example of multiplicative seasonality the season is… Read More »
This is a guest blog entry by Fotios Petropoulos. A few months ago, Bergmeir, Hyndman and Benitez made available a very interesting working paper titled “Bagging exponential smoothing methods using STL decomposition and Box-Cox transformation”. In short, they successfully employed the bootstrap aggregation technique for improving the performance of exponential smoothing. The bootstrap technique is… Read More »
In my experience users of exponential smoothing have often limited transparency in how the various smoothing parameters interact. I built this small demo to illustrate how the different smoothing parameters and exponential smoothing components interact. You can choose between some simulated and some real time series, as well as the option to add outliers or… Read More »
Every year the International Institute of Forecasters (IIF) in collaboration with SAS has been supporting forecasting research with grants up to $5,000. The application deadline for this year is the 30th of September 2014. Applications must include: Description of the project, up to 4 pages; Letter of support from the home institution that the researcher… Read More »