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Lawsuits of a workshop backed by means of the commercial and Social learn Council.
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1975). The Delphic Method: Techniques and Applications. F. et al. (1975). Forecasting for water resources management in the Canadian North. Water and Pollution Control, 113, 6–9. Mahmoud, E. (1984). Accuracy in forecasting: a survey. Journal of Forecasting, 3, 139–59. Makridakis, S. et al. (1982). The accuracy of extrapolation (time series) methods: results of a forecasting competition. Journal of Forecasting, 1, 111–53. Million, G. (1980). D. ) Forecasting Public Utilities, 9–15. L. (1971). Forecasting electricity sales.
Forecasting electricity sales. The Statistician, 20, 15–22. J. et al. (1984). An examination of factors contributing to Delphic accuracy. Journal of Forecasting, 3, 173–82. C. (1980). S. ), Atlas of Drought in Britain 1975–6, Institute of British Geographers, London, 67–8. A. et al. (1981). Deterministic models for predicting residential water consumption. Water Resources Bulletin, 17, 1042–9. A. and Rees, R. (1972). Water demand forecasts and planning margins in South-East England. Regional Studies, 6, 37–48.
1982) carried out a large-scale empirical study in which 1001 time series were examined by 24 methods. They confirm the generally accepted wisdom that more complex or sophisticated methods are not necessarily more accurate than simpler ones, and hypothesise that sophisticated methods do not perform better than simpler ones where there is considerable randomness in the data. Accuracy is not, of course, the only criterion of interest, and the choice of method must also depend upon the type of data, type of series and time horizon of the forecast, as well as upon budgetary constraints.