As for my contribution, I presented a paper that Nikos Kourentzes and I have been working on since around 2018. It focuses on pooling using point information criteria. The core idea is to combine forecasts based on a smaller pool of models, which we propose creating by comparing the distributions of information criteria across forecasting models. We’re planning to finish a new version of the paper by September and submit it to a peer-reviewed journal. I’ll share more details when the draft that I can share is ready. In the meantime, you can check out the slides that summarise the main points of the paper. Here they are.

Message ITISE2025: Beyond summary performance metrics for forecast selection and combination first appeared on Open Forecasting.

First things first, the event was organised by Mitchell O’Hara, Xiaoqian Wang, Bahman Rostami-Tabar, Azul Garza, Resul Akay, Shanika Wickramasuriya and me. My contribution was acting as the programme chair of the workshop and helping invite some speakers. The event was sponsored by the International Institute of Forecasters, and you can find some information about it on the following website. The workshop lasted for two days, and there were several great talks delivered by excellent speakers (see the full programme here).

But among those, there were two talks especially important to me personally, because they were related to the smooth package:

1. by Kandrika Pritularga, explaining the core of the package, the maths behind it, and how it works,
2. by Filotas Theodosiou, who explained his excellent work on translating the smooth R code to Python.

Yes, you’ve heard correctly! We have finally had some progress translating the smooth package from R to Python (done between Filotas, Leonidas Tsaprounis and me. I’m a vibe coder now! :D). The Python code is available in this GitHub branch, and we now even have a description of the package structure and function flow (thanks to Fil and his AI friends).

It’s still a work in progress, and there’s lots to do, but it’s an important step for us. We plan to continue working on it, and there are already several people who have started helping us with the translation. So, stay tuned – great times are coming!

Message IIF Open Source Forecasting software workshop and smooth first appeared on Open Forecasting.

My presentation was based on this paper. And here are the slides:
2025-05-01-IMA-OR

Message 5th IMA and OR Society Conference first appeared on Open Forecasting.

Abstract: Bootstrap is extensively used in statistics and machine learning for cross-sectional data to account for uncertainty about the data, model form, and parameter estimates. However, conventional methods may not be suitable for time series data due to autocorrelation and specific dynamic structures. Over the years, various approaches have been developed to address this issue. Some assume specific models (e.g., STL), while others are non-parametric (e.g., Maximum Entropy Bootstrap, MEB). However, the former can be overly restrictive, while the latter may not perform well in case of outliers and external drivers. To address these issues, we propose a non-parametric bootstrap approach inspired by MEB, which does not assume any structure in the data yet creates reasonable copies of existing time series of different nature. These copies can be utilised in bagged ETS/ARIMA or any other approach involving small sample uncertainty. We demonstrate how the proposed bootstrap works using real-time series examples and assess improvements it brings in terms of forecasting accuracy compared to conventional approaches.

Here are the slides of the presentation.

And here is me, trying not to attract attention of statisticians:

How to attract attention of statisticians…

Message ISF2024: How to Bootstrap Time Series without Attracting Attention of Statisticians first appeared on Open Forecasting.

ETS+ARIMA love story with happy ending…

This talk was based on Chapter 9 of ADAM monograph, and more specifically on Section 9.4.

The slides of the presentation are available here.

Message ISF2022: How to make ETS work with ARIMA first appeared on Open Forecasting.

Presentation at ISF2021 Lancaster Hub

I presented on the topic of Multiplicative ETS, based on this chapter of the ADAM textbook and on the paper John Boylan and I are working on. In this presentation, I discuss that the point forecasts from the ETS(M,*,*) models in general do not correspond to conditional expectations (and not even to geometric means) and show the difference between the two. Furthermore, we propose using Log Normal, Gamma and Inverse Gaussian distributions for the error term of the model instead of the Normal one. This makes the model more realistic and help in forecasting on low volume data. All of this is already implemented in adam() function of smooth package for R.

Here are the slides.

Message ISF2021: How to Make Multiplicative ETS Work for You first appeared on Open Forecasting.

The slides of the presentation are available here.

Message Multi-step Estimators and Shrinkage Effect in Time Series Models – presentation for CEBA first appeared on Open Forecasting.

Retail sales of tomatoes

Anyway, here are the slides if anyone wants to have a look.

Message International Symposium on Forecasting 2019 first appeared on Open Forecasting.

1. State space ARIMA for Supply Chain Forecasting, based on which I have developed a module for Smoothie a couple of years ago,
2. Artificial Intelligence in Business, one of the modern hot topics that the company wanted to know a little bit more about.

Presentation at SMUG2019

The conference was interesting, showing what the company does and what it stands for. They are doing a good job in developing the software for forecasting and inventory control and supporting their users. Plus, I finally had a chance to meet in person with both founders of the company (Bill Tonetti and Eric Townson), as well as with the other members of their team. Overall, it was a pleasant experience and an interesting event.

As for the presentations, they seemed to go well, and the participants of the conference looked satisfied. Here are the slides:

1. SMUG2019 – Svetunkov – ARIMA
2. SMUG2019 – Svetunkov – AI in Business

Message SMUG2019 first appeared on Open Forecasting.

1. 5th April, CMAF Workshop on Retail Demand Forecasting and Data Science, London UK. This is an event organised by the Centre for Marketing Analytics and Forecasting of Lancaster University, UK. This is focused on practitioners. Anyone interested can register on the website and attend, this is a free event.
2. 29th April, CMAF Workshop on Business Forecasting using R: Are we there yet? London, UK. This is also organised by CMAF and this is also a free event. The workshop might be interesting to practitioners who want to know more about R, how to use it for decision making and whether it is worth investing in support systems based on R.
3. 23 – 24th May, 25th IIF Workshop: Predictive Analytics: Theory, Applications and Algorithms, Cambridge, UK. This is the workshop organised by the International Institute of Forecasters. It should be interesting to the forecasting and machine learning audiences.
4. 3 – 5th September, Forecasting stream at OR61, Kent University, UK. The stream is organised by Robert Fildes and John Boylan. It’s too early to say who specifically will be there, but the OR conferences are usually quite versatile and are interesting to attend.

You can still attend the following events:

1. 16 – 19th June, 39th International Symposium on Forecasting in Thessaloniki, Greece. I am presenting on the topic of intermittent demand and also co-authoring three other talks (on vector exponential smoothing, on hierarchical forecasting and on complex-valued modelling).
2. 20 – 22nd June, ISMS Marketing Science Conference 2019, Rome, Italy. I won’t attend this myself, but some of my colleagues are going. This should be an interesting event, taking place in a great city.
3. 9 – 12th July, useR!, Toulouse, France. I will be presenting the functions of smooth package and I will be giving the hex stickers for smooth and greybox packages for free at this event. So if you have spaces on your laptop that you don’t know how to fill in, going to Toulouse and getting hexes is the best thing you can do this summer…

Hopefully, I will be able to come up with the next post like this some time before the end of 2019.

Message Conferences 2019 first appeared on Open Forecasting.