Synthesis or selection of forecasting models |
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Authors: | DW Bunn E Kappos |
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Institution: | Department of Engineering Science, University of Oxford, Oxford 0X1 3PJ, United Kingdom;Massachusetts Institute of Technology, Cambridge, MA, U.S.A. |
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Abstract: | This report is relevant to the practical forecasting situation in which a decision-maker is faced with several feasible predictors for his variable of interest. If he has a substantial amount of data available on the performance of each of his predictors, then it is well known that a composite forecast can be suitably derived as an optimal forecasting procedure. Alternatively, if only a small amount of evidence is available on the predictors' performance, then there appear to be controversial recommendations upon whether it is still optimal to pursue a policy of synthesis leading to a composite predictor or whether it is better to attempt a selection of the singularly best forecasting model. This report discusses some of the associated issues and provides some experimental evidence on the performance of these two policies. |
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