The well-calibrated Bayesian¶
Dawid, A. P. (1982). The well-calibrated Bayesian. Journal of the American Statistical Association, 77(379), 605-610.
Cited by¶
1 citation across 1 artifact.
Each citation links to the sentence it supports in the citing article.
Primes¶
- Calibration
- The structural insight applies across domains: a physicist calibrating a spectrometer, a data scientist calibrating a classifier, and an organization calibrating performance metrics all follow the same template of reference-deviation-adjustment, as Dawid (1982) formalized in his account of the well-calibrated forecaster across substrates.
This sourceFoundational statistical formalization of calibration as a substrate-agnostic property: a forecaster is well calibrated if, of events assigned probability p, the long-run proportion that occur is p; proves a coherent Bayesian expects to be well calibrated.
- The structural insight applies across domains: a physicist calibrating a spectrometer, a data scientist calibrating a classifier, and an organization calibrating performance metrics all follow the same template of reference-deviation-adjustment, as Dawid (1982) formalized in his account of the well-calibrated forecaster across substrates.
Verification¶
This reference passed the adversarial substantiation pipeline: it was checked to exist and to support the claim it is attached to. See how references were verified.
Registry ID ref:5b82f5c61035 · see in the full table