I have been asked recently by a colleague of mine how to extract the variance from a model estimated using adam() function from the smooth package in R. The problem was that that person started reading the source code of the forecast.adam() and got lost between the lines (this happens to me as well sometimes). […]
R
Detecting patterns in white noise
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 […]
smooth & greybox under LGPLv2.1
Good news, everyone! I’ve recently released major versions of my packages smooth and greybox, v4.0.0 and v2.0.0 respectively, on CRAN. Has something big happened? Yes and no. Let me explain. Starting from these versions, the packages will be licensed under LGPLv2.1 instead of the very restrictive GPLv2. This does not change anything to the everyday […]
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 […]
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 […]
Smooth forecasting with the smooth package in R
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 […]
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 […]