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Shrinkage estimator for exponential smoothing models
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- Pritularga, Kandrika F. (author)
- Centre for Marketing Analytics and Forecasting, Department of Management Science, Lancaster University Management School, United Kingdom
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- Svetunkov, Ivan (author)
- Centre for Marketing Analytics and Forecasting, Department of Management Science, Lancaster University Management School, United Kingdom
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- Kourentzes, Nikolaos (author)
- Högskolan i Skövde,Institutionen för informationsteknologi,Forskningsmiljön Informationsteknologi,Skövde Artificial Intelligence Lab (SAIL)
- (creator_code:org_t)
- Elsevier, 2023
- 2023
- English.
- In: International Journal of Forecasting. - : Elsevier. - 0169-2070 .- 1872-8200. ; 39:3, s. 1351-1365
- Journal article (peer-reviewed)
Abstract
Subject headings
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- Exponential smoothing is widely used in practice and has shown its efficacy and reliability in many business applications. Yet there are cases, for example when the estimation sample is limited, where the estimated smoothing parameters can be erroneous, often unnecessarily large. This can lead to over-reactive forecasts and high forecast errors. Motivated by these challenges, we investigate the use of shrinkage estimators for exponential smoothing. This can help with parameter estimation and mitigating parameter uncertainty. Building on the shrinkage literature, we explore ℓ1 and ℓ2 shrinkage for different time series and exponential smoothing model specifications. From a simulation and an empirical study, we find that using shrinkage in exponential smoothing results in forecast accuracy improvements and better prediction intervals. In addition, using bias–variance decomposition, we show the interdependence between smoothing parameters and initial values, and the importance of the initial value estimation on point forecasts and prediction intervals.
Subject headings
- NATURVETENSKAP -- Matematik -- Sannolikhetsteori och statistik (hsv//swe)
- NATURAL SCIENCES -- Mathematics -- Probability Theory and Statistics (hsv//eng)
Keyword
- 42
- ETS
- Forecasting
- Parameter estimation
- Regularisation
- State-space model
- Skövde Artificial Intelligence Lab (SAIL)
- Skövde Artificial Intelligence Lab (SAIL)
Publication and Content Type
- ref (subject category)
- art (subject category)
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