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|a ED135799 Microfiche
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|a Brown, Thomas A.
|0 http://id.loc.gov/authorities/names/n94083371
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|a Admissible Scoring Systems for Continuous Distributions /
|c Thomas A. Brown.
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|a [Place of publication not identified] :
|b Distributed by ERIC Clearinghouse,
|c 1974.
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|a 27 pages
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|a text
|b txt
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|a Availability: The Rand Corporation, 1700 Main Street, Santa Monica, California 90406 (P-5235, $1.50).
|5 ericd
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|a The defining property of an admissible scoring system is that any individual perceives himself as maximizing his expected score by reporting his true subjective distribution. The use of admissible scoring systems as a measure of probabilistic forecasts is becoming increasingly well-known in those cases where the forecast is a discrete distribution over a finite number of alternatives. Most serious forecasts which are made in the real world seem to be forecasts of quantities rather than choices between a finite number of alternatives. In such cases as this, it seems much more natural to ask the forecaster to specify a continuous probability distribution which represents his expectations rather than trying to re-cast a basically continuous process into a discrete one. To construct an admissible scoring system for a continuous distribution, a collection of possible bets can be postulated on a continuous variable, and an admissible scoring system can be constructed as the net pay-off to a forecaster who takes all bets (and only those bets) which appear favorable on the basis of his reported distribution. Mathematical models for this and alternative systems are presented. (Author/BW)
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|a Microfiche.
|b [Washington D.C.]:
|c ERIC Clearinghouse
|e microfiches : positive.
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|a Microform.
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|a Mathematical Models.
|2 ericd
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|a Prediction.
|2 ericd
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|a Probability.
|2 ericd
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|a Scoring.
|2 ericd
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|a Statistics.
|2 ericd
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|a Admissible Probability Testing
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|a Reports, Research.
|2 ericd
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|a Rand Corporation.
|0 http://id.loc.gov/authorities/names/n78083407
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|a Michigan State University-Library of Michigan
|b Michigan State University
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