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    Integration of multi-time-scale models in time series forecasting

    Murray, Fiona T. and Ringwood, John and Austin, Paul C. (2000) Integration of multi-time-scale models in time series forecasting. International Journal of Systems Science, 31 (10). pp. 1249-1260. ISSN 0020-7721

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    A solution to the problem of producing long-range forecasts on a short sampling interval is proposed. It involves the incorporation of information from a long sampling interval series, which could come from an independent source, into forecasts produced by a state-space model based on a short sampling interval. The solution is motivated by the desire to incorporate yearly electricity consumption information into weekly electricity consumption forecasts. The weekly electricity consumption forecasts are produced by a state-space structural time series model. It is shown that the forecasts produced by the forecasting model based on weekly data can be improved by the incorporation of longer-tim e-scale information, particularly when the forecast horizon is increased from 1 year to 3 years. A further example is used to demonstrate the approach, where yearly UK primary fuel consumption information is incorporated into quarterly fuel consumption forecasts.

    Item Type: Article
    Keywords: multi-time-scale models; time series forecasting; long range forecasts; electricity consumption forecasts;
    Academic Unit: Faculty of Science and Engineering > Electronic Engineering
    Item ID: 9511
    Identification Number:
    Depositing User: Professor John Ringwood
    Date Deposited: 06 Jun 2018 13:58
    Journal or Publication Title: International Journal of Systems Science
    Publisher: Taylor & Francis
    Refereed: Yes
    Use Licence: This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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