This time ISF took place in Oxford. I acted as a programme chair of the event and was quite busy with schedule and some other minor organisational things, but I still found time to present something new. Specifically, I talked about one specific part of ADAM, the part implementing ETS+ARIMA. The idea is that the … Read more
After working on this for more than a year, I have finally prepared the first draft of my online monograph “Forecasting and Analytics with ADAM“. This is a monograph on the model that unites ETS, ARIMA and regression and introduces advanced features in univariate modelling, including: ETS in a new State Space form; ARIMA in … Read more
My student (co-supervised with Nikos Kourentzes), Kandrika F. Pritularga has written a paper on “Stochastic coherency in forecast reconciliation”, which has been recently published in International Journal of Production Economics (here it is). This paper contributes to the field of hierarchical forecasting, the main issue of which is that the forecasts produced on different levels … Read more
Today I have made a presentation on the topic of “Multi-step Estimators and Shrinkage Effect in Time Series Models” for Center for Econometrics and Business Analytics (CEBA) of St.Petersburg State University. This presentation was based on the paper with the similar name written by Ivan Svetunkov, Nikolaos Kourentzes and Rebecca Killick. In the presentation, I … Read more
Since the previous post on “The Creation of ADAM“, I had difficulties finding time to code anything, but I still managed to fix some bugs, implement a couple of features and make changes, important enough to call the next version of package smooth “3.1.0”. Here is what’s new: A new algorithm for ARIMA order selection … Read more
Good news everyone! The future of statistical forecasting is finally here :). Have you ever struggled with ETS and needed explanatory variables? Have you ever needed to unite ARIMA and ETS? Have you ever needed to deal with all those zeroes in the data? What about the data with multiple seasonalities? All of this and … Read more
I was recently invited to attend the SMUG2019 conference (SMoothie Users Group), organised by Demand Works company in New York. They asked me to present two topics: State space ARIMA for Supply Chain Forecasting, based on which I have developed a module for Smoothie a couple of years ago, Artificial Intelligence in Business, one of … Read more
Fotios Petropoulos and I have participated last year in M4 competition. Our approach performed well, finishing as 6th in the competition. This paper in International Journal of Forecasting explains what we used in our approach and why. Here’s the abstract: This paper describes the approach that we implemented for producing the point forecasts and prediction … Read more
John Boylan and I have been working lately on a paper, explaining the logic behind the ssarima() function from the smooth package. This paper has finally been accepted and published. Also, based on a modified version of the ssarima() function, I have developed a SSARIMA module for Smoothie software, developed by DemandWorks company. Both the … Read more
One of the features of the functions in smooth package is the ability to use exogenous (aka “external”) variables. This potentially leads to the increase in the forecasting accuracy (given that you have a good estimate of the future exogenous variable). For example, in retail this can be a binary variable for promotions and we … Read more