Beneki, Christina and Silva, E.S. (2013) Analysing and forecasting European Union energy data. International Journal of Energy and Statistics, 1 (2). pp. 127-141. ISSN 2335-6812
Type of Research: | Article |
---|---|
Creators: | Beneki, Christina and Silva, E.S. |
Description: | The incessantly growing demand for energy consumption and the significance of the availability of sustainable energy for achieving long term economic growth defines the importance of forecasting energy statistics. This paper analyses and forecasts actual energy consumption data for EU-27 nations using both parametric and nonparametric time series forecasting techniques. Singular Spectrum Analysis (SSA) is adopted as the nonparametric time series analysis and forecasting technique and the results from SSA are compared with ARIMA, which is a parametric forecasting technique. |
Additional Information (Publicly available): | This article is on restricted access due to copyright restrictions. Please contact UAL Research Online to request access. |
Keywords/subjects not otherwise listed: | Energy, Forecast, Electricity consumption; Renewable electricity consumption; Primary energy consumption; Forecasting; Singular Spectrum Analysis; ARIMA; Parametric; Nonparametric |
Your affiliations with UAL: | Colleges > London College of Fashion |
Date: | 5 July 2013 |
Digital Object Identifier: | 10.1142/S2335680413500099 |
Date Deposited: | 28 Jun 2016 11:30 |
Last Modified: | 28 Apr 2017 14:10 |
Item ID: | 9549 |
URI: | https://ualresearchonline.arts.ac.uk/id/eprint/9549 |
Repository Staff Only: item control page | University Staff: Request a correction