The DOI matches its Crossref record; 24 of the 24 references it cites were found in a registry or an index.
The Well-Calibrated Bayesian
Abstract
Suppose that a forecaster sequentially assigns probabilities to events. He is well calibrated if, for example, of those events to which he assigns a probability 30 percent, the long-run proportion that actually occurs turns out to be 30 percent. We prove a theorem to the effect that a coherent Bayesian expects to be well calibrated, and consider its destructive implications for the theory of coherence.
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Cited by
Sorted by citations
Prediction, Learning, and Games
Cesa‐Bianchi, N., & Lugosi, G. (2006) · Cambridge University Press eBooks · doi:10.1017/cbo9780511546921 · Cited by 3,338
“It was Dawid [80] who introduced the problem to the literature of mathematical statistics – see also Dawid’s related work on calibration and “prequential” statistics [81, 82, 84].”
BackgroundThe weighing of evidence and the determinants of confidence
Griffin, D., & Tversky, A. (1992) · Cognitive Psychology · doi:10.1016/0010-0285(92)90013-r · Cited by 1,866
“This objection, however, overlooks the fact that a Bayesian expects to be calibrated (Dawid, 1982), hence the theory of subjective probability permits the comparison of confidence and accuracy.”
Probabilistic Forecasts, Calibration and Sharpness
Gneiting, T., Balabdaoui, F., & Raftery, A. E. (2007) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.1467-9868.2007.00587.x · Cited by 1,783
“Various researchers have studied calibration in the context of probability forecasts for sequences of binary events (DeGroot and Fienberg, 1982; Dawid, 1982, 1985a, b; Oakes, 1985; Schervish, 1985, 1989; Dawid and Vovk, 1999; Shafer and Vovk, 2001; Sandroni et al., 2003).”
BackgroundFeng, D., Haase-Schutz, C., Rosenbaum, L., Hertlein, H., Glaser, C., Timm, F., Wiesbeck, W., & Dietmayer, K. (2021) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2020.2972974 · Cited by 1,425
“empirical calibration curves [204] and log predictive probabilities.”
BackgroundForecast verification : a practitioner's guide in atmospheric science
Jolliffe, I., & Stephenson, D. (2011) · Wiley eBooks · doi:10.1002/9781119960003 · Cited by 1,457
Metadata
- Authors
- Dawid, A. P.
- Affiliations
- University College London (GB)
- Corresponding author
- Dawid, A. P.
- ORCID
- Dawid, A. P.
- Venue
- Journal of the American Statistical Association
- Publisher
- Informa UK Limited
- Published
- 1982-09
- Volume
- 77
- Issue
- 379
- Pages
- 605-610
- ISSN
- 0162-1459 (ISSN-L)
- 1537-274X
- OpenAlex
- W2023943903
- Cited by
- 625
- References
- 24
- Citations by year
- 2026: 22 · 2025: 26 · 2024: 45 · 2023: 51 · 2022: 27 · 2021: 31 · 2020: 39 · 2019: 18 · 2018: 19 · 2017: 15 · 2016: 13 · 2015: 18 · 2014: 23 · 2013: 18 · 2012: 17
- FWCI
- 6.76
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of the American Statistical Association (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Bayesian Modeling and Causal Inference
- Physical Sciences › Mathematics › Statistics and Probability › Probability and Statistical Research
- Social Sciences › Decision Sciences › Management Science and Operations Research › Forecasting Techniques and Applications
- Keywords
- well calibration, Bayesian forecasting, coherence, subjective probability, Dutch book argument
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