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 »
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 »
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 »
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 »
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 »
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 »
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 »
I uploaded a new version (1.7) of tsintermittent on CRAN. Apart from fixing a couple of minor issues, a new function has been added to help scaling up forecasting. Recently I had a few requests to add a functionality to use data frames with multiple time series as inputs. I have included a new wrapper… Read More »
The International Institute of Forecasters (IIF), in collaboration with SAS, offer financial support research on improving forecasting methods and business forecasting practice. TThis year there will be two grants of $5,000 . The deadline date for applications is September 30, 2015. This grant was created in 2002 by the IIF, with financial support from the… Read More »
Last week had been very busy at the 27th European Conference on Operational Research. Within the Analytics, Data Science, Data Mining stream there was a specialised stream on Forecasting & Time Series Prediction that was very successfully organised by Sven F. Crone and Aris Syntetos. The talks have been stimulating and of a high level. Given… Read More »