Cognitive Foundations of Probability
AbstractPrediction 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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Bibliographic InfoPaper provided by Tel Aviv in its series Papers with number 30-99.
Length: 46 pages
Date of creation: 1999
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Postal: Israel TEL-AVIV UNIVERSITY, THE FOERDER INSTITUTE FOR ECONOMIC RESEARCH, RAMAT AVIV 69 978 TEL AVIV ISRAEL.
Web page: http://econ.tau.ac.il/research/foerder.asp
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- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
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- Enriqueta Aragones & Itzhak Gilboa & Andrew Postlewaite & David Schmeidler, 2003.
"Accuracy vs. Simplicity: A Complex Trade-Off,"
UFAE and IAE Working Papers
564.03, Unitat de Fonaments de l'Anàlisi Econòmica (UAB) and Institut d'Anàlisi Econòmica (CSIC).
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