Prediction is based on past cases. We assume that a predictor can rank eventualities according to their plausibility given any memory that consists of repetitions of past cases. In a companion paper, we show that under mild consistency requirements, these rankings can be represented by numerical functions, such that the function corresponding to each eventuality is linear in the number of case repetitions. In this paper we extend the analysis to rankings of events. Our main result is that a cancellation condition a la de Finetti implies that these functions are additive with respect ot union of disjoint sets.
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Paper provided by Tel Aviv in its series Papers with number
30-99.
Find related papers by JEL classification: C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Other Model Applications C60 - Mathematical and Quantitative Methods - - Mathematical Methods and Programming - - - General
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