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- Title
Entropy Application for Forecasting.
- Authors
López-Menéndez, Ana Jesús; Pérez-Suárez, Rigoberto
- Abstract
Keywords: information theory; uncertainty; forecasting methods; forecasting evaluation; accuracy; M-competition; combined forecasts; scenarios EN information theory uncertainty forecasting methods forecasting evaluation accuracy M-competition combined forecasts scenarios 604 1 07/11/20 20200601 NES 200601 The information theory developed by Shannon [[1]] defines the entropy for any probabilistic system as a measure of the related uncertainty. A great diversity is also observed in the methods, since the contributions encompass a wide variety of time series techniques (ARIMA, VAR, State Space Models, etc.) as well as econometric methods and machine learning algorithms. Information theory, uncertainty, forecasting methods, forecasting evaluation, accuracy, M-competition, combined forecasts, scenarios.
- Subjects
INFORMATION theory; UNCERTAINTY (Information theory); DEMAND forecasting; INFORMATION theory in economics; ENTROPY (Information theory)
- Publication
Entropy, 2020, Vol 22, Issue 6, p604
- ISSN
1099-4300
- Publication type
Editorial
- DOI
10.3390/e22060604