The use of admissible scoring systems for discrete probabilistic forecasts is familiar to weather forecasters and has often been proposed as a new technique in intelligence and educational testing. However, many forecasting tasks involve predicting a number (from a very large set of possibilities) rather than choosing one of a small, discrete set of contingencies. This paper presents three alternative techniques for generating admissible scoring systems which may be applied to such "continuous" (as opposed to "discrete") forecasting tasks.
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