Back in 2015, when I was working on my paper on Complex Exponential Smoothing, I conducted a simple simulation experiment to check how ARIMA and ETS select components/orders in time series. And I found something interesting… One of the important steps in forecasting with statistical models is identifying the existing structure. In the case of […]
Univariate models
What’s wrong with ARIMA?
Have you heard of ARIMA? It is one of the benchmark forecasting models used in different academic experiments, although it is not always popular among practitioners. But why? What’s wrong with ARIMA? ARIMA has been a standard forecasting model in statistics for ages. It gained popularity with the famous Box & Jenkins (1970) book and […]
Why you should not use Holt-Winters method
Whenever I see results of an experiment that include Holt-Winters method, I shrug. You should not use it, and here is why. Holt-Winters was developed in 1960 by a student of Charles Holt, Peter Winters (Winters, 1960). He extended Holt’s exponential smoothing method (the method that introduced a trend component) to include a seasonal component. […]
Staying Positive: Challenges and Solutions in Using Pure Multiplicative ETS Models
Authors: Ivan Svetunkov, John E. Boylan Journal: IMA Journal of Management Mathematics Abstract: Exponential smoothing in state space form (ETS) is a popular forecasting technique, widely used in research and practice. While the additive error ETS models have been well studied, the multiplicative error ones have received much less attention in forecasting literature. Still, these […]
Why you should care about Exponential Smoothing
On 15th December 2023, I presented in a CMAF Friday Forecasting Talks webinar on the topic of “Why you should care about exponential smoothing”. The motivation was to give a fresh view on the good old model and show how it started, how it evolved over time and how it can be improved. With this […]
iETS: State space model for intermittent demand forecasting
Authors: Ivan Svetunkov, John E. Boylan Journal: International Journal of Production Economics Abstract: Inventory decisions relating to items that are demanded intermittently are particularly challenging. Decisions relating to termination of sales of product often rely on point estimates of the mean demand, whereas replenishment decisions depend on quantiles from interval estimates. It is in this […]
Multi-step Estimators and Shrinkage Effect in Time Series Models
Authors: Ivan Svetunkov, Nikos Kourentzes, Rebecca Killick Journal: Computational Statistics Abstract: Many modern statistical models are used for both insight and prediction when applied to data. When models are used for prediction one should optimise parameters through a prediction error loss function. Estimation methods based on multiple steps ahead forecast errors have been shown to […]
Story of “Probabilistic forecasting of hourly emergency department arrivals”
The paper Back in 2020, when we were all siting in the COVID lockdown, I had a call with Bahman Rostami-Tabar to discuss one of our projects. He told me that he had an hourly data of an Emergency Department from a hospital in Wales, and suggested writing a paper for a healthcare audience to […]
Probabilistic forecasting of hourly emergency department arrivals
Authors: Bahman Rostami-Tabar, Jethro Browell, Ivan Svetunkov Journal: Health Systems Abstract: An accurate forecast of Emergency Department (ED) arrivals by an hour of the day is critical to meet patients’ demand. It enables planners to match ED staff to the number of arrivals, redeploy staff, and reconfigure units. In this study, we develop a model […]
smooth v3.2.0: what’s new?
smooth package has reached version 3.2.0 and is now on CRAN. While the version change from 3.1.7 to 3.2.0 looks small, this has introduced several substantial changes and represents a first step in moving to the new C++ code in the core of the functions. In this short post, I will outline the main new […]