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

نویسندگان

  • Fiona T. Murray
  • John V. Ringwood
  • Paul C. Austin
چکیده

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-time-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.

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عنوان ژورنال:
  • Int. J. Systems Science

دوره 31  شماره 

صفحات  -

تاریخ انتشار 2000