Authors: Ivan Svetunkov Abstract: There are many forecasting related packages in R with varied popularity, the most famous of all being forecast, which implements several important forecasting approaches, such as ARIMA, ETS, TBATS and others. However, the main issue with the existing functionality is the lack of flexibility for research purposes, when it comes to […]
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Complex Exponential Smoothing
Authors: Ivan Svetunkov, Nikolaos Kourentzes, Keith Ord. Journal: Naval Research Logistics Abstract: Exponential smoothing has been one of the most popular forecasting methods used to support various decisions in organisations, in activities such as inventory management, scheduling, revenue management and other areas. Although its relative simplicity and transparency have made it very attractive for research […]
ISF2022: How to make ETS work with ARIMA
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 […]
The first draft of “Forecasting and Analytics with ADAM”
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 […]
Introducing scale model in greybox
At the end of June 2021, I released the greybox package version 1.0.0. This was a major release, introducing new functionality, but I did not have time to write a separate post about it because of the teaching and lack of free time. Finally, Christmas has arrived, and I could spend several hours preparing the […]
An Integrated Method for Estimation and Optimisation
My PhD student, Congzheng Liu (co-supervised with Adam Letchford) has written a paper, entitled “Newsvendor Problems: An Integrated Method for Estimation and Optimisation“. This paper has recently been published in EJOR. In this paper we build upon the existing Ban & Rudin (2019) approach for newsvendor problem, showing that in case of the linear model, […]
After the creation of ADAM: smooth v3.1.0
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 […]
The creation of ADAM – next step in statistical forecasting
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 […]
Accuracy of forecasting methods: Can you tell the difference?
Previously we discussed how to measure accuracy of point forecasts and performance of prediction intervals in different cases. Now we look into the question how to tell the difference between competing forecasting approaches. Let’s imagine the situation, when we have four forecasting methods applied to 100 time series with accuracy measured in terms of RMSSE: […]
How confident are you? Assessing the uncertainty in forecasting
Introduction Some people think that the main idea of forecasting is in predicting the future as accurately as possible. I have bad news for them. The main idea of forecasting is in decreasing the uncertainty. Think about it: any event that we want to predict has some systematic components \(\mu_t\), which could potentially be captured […]