If you work in the field of statistics, analytics, data science or forecasting, then you probably have already noticed that some of the instruments that are used in your field are called “methods”, while the others are called “models”. The issue here is that the people, using these terms, usually know the distinction between them, … Read more
UPDATE: Read more about intermittent demand in newer posts: Introduction to intermittent demand Do you really need SBC? Lumpy is a type of intermittent demand and the usefulness of the classification scheme; And there is more, check the Intermittent Demand category on the website. In one of the previous posts, we have discussed how to … Read more
Two years ago I have written a post “Naughty APEs and the quest for the holy grail“, where I have discussed why percentage-based error measures (such as MPE, MAPE, sMAPE) are not good for the task of forecasting performance evaluation. However, it seems to me that I did not explain the topic to the full … Read more
One of the basic things the students are taught in statistics classes is that the comparison of models using information criteria can only be done when the models have the same response variable. This means, for example, that when you have \(\log(y_t)\) and calculate AIC, then this value is not comparable with AIC from a … Read more
Yesterday I gave a lecture to the master students of Higher School Economics, Saint Petersburg (“Marketing Analytics” programme). This was a very general lecture on “Modern Forecasting”, covering forecasting problems in practice, the solutions to these problems and modern scientific directions in the field. It seems that the lecture was well received and brought up … Read more
Today I want to tell you a story of naughty APEs and the quest for the holy grail in forecasting. The topic has already been known for a while in academia, but is widely ignored by practitioners. APE stands for Absolute Percentage Error and is one of the simplest error measures, which is supposed to … Read more
An IIF workshop “Supply Chain Forecasting for Operations” took place at Lancaster University on 28th and 29th of June. I have given a presentation on a topic that John Boylan and I are currently working on. We suggest a universal statistical model, that allows uniting standard methods of forecasting (for example, for fast moving products) … Read more
In the modern statistical literature there is a notion of “true model”, by which people usually mean some abstract mathematical model, presumably lying in the core of observed process. Roughly saying, it is implied that data we have has been generated by some big guy with a white beard sitting in mathematical clouds using some … Read more
This Wednesday Stephan Kolassa (Senior Research Expert at SAP) has visited Lancaster Centre for Forecasting. He gave a couple of very interesting talks and attended the presentation of PhD topics by Ivan Svetunkov, Yves Sagaert and Oliver Schaer (organised by Nikolaos Kourentzes). My topic was “Trace Forecast Likelihood”, some parts of which I have presented … Read more
Some time ago I have published the working paper on Complex Exponential Smoothing on ResearchGate website. This is the paper written by Nikolaos Kourentzes and I in 2015. It explains a new approach in time series modelling and in forecasting, based on a notion of “information potential”. The model, resulting from this idea, allows to … Read more