Framing the issue of subjective probability calibration in signal-detectiontheory terms, this paper first proves a theorem regarding the placement of well-calibrated response criteria and then develops an algorithm guaranteed to find such criteria, should they exist. Application of this algorithm to
Evaluating and Combining Subjective Probability Estimates
โ Scribed by THOMAS S. WALLSTEN; DAVID V. BUDESCU; IDO EREV; ADELE DIEDERICH
- Publisher
- John Wiley and Sons
- Year
- 1997
- Tongue
- English
- Weight
- 297 KB
- Volume
- 10
- Category
- Article
- ISSN
- 0894-3257
No coin nor oath required. For personal study only.
โฆ Synopsis
This paper concerns the evaluation and combination of subjective probability estimates for categorical events. We argue that the appropriate criterion for evaluating individual and combined estimates depends on the type of uncertainty the decision maker seeks to represent, which in turn depends on his or her model of the event space. Decision makers require accurate estimates in the presence of aleatory uncertainty about exchangeable events, diagnostic estimates given epistemic uncertainty about unique events, and some combination of the two when the events are not necessarily unique, but the best equivalence class deยฎnition for exchangeable events is not apparent. Following a brief reveiw of the mathematical and empirical literature on combining judgments, we present an approach to the topic that derives from (1) a weak cognitive model of the individual that assumes subjective estimates are a function of underlying judgment perturbed by random error and (2) a classiยฎcation of judgment contexts in terms of the underlying information structure. In support of our developments, we present new analyses of two sets of subjective probability estimates, one of exchangeable and the other of unique events. As predicted, mean estimates were more accurate than the individual values in the ยฎrst case and more diagnostic in the second.
๐ SIMILAR VOLUMES
The paper reports results of an experiment conducted to evaluate subjective versus objective combination of forecasts. The subjects were undergraduate students at Texas A&M. The students forecasted two different types of time series. The results found show that the subjective combination of forecast