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- W2023943903 abstract "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." @default.
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- W2023943903 date "1982-09-01" @default.
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- W2023943903 title "The Well-Calibrated Bayesian" @default.
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- W2023943903 doi "https://doi.org/10.1080/01621459.1982.10477856" @default.
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