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Failure of Calibration is Typical

Belot, Gordon (2013) Failure of Calibration is Typical. [Preprint]

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    Abstract

    Schervish (1985b) showed that every forecasting system is noncalibrated for uncountably many data sequences that it might see. This result is strengthened here: from a topological point of view, failure of calibration is typical and calibration rare. Meanwhile, Bayesian forecasters are certain that they are calibrated---this invites worries about the connection between Bayesianism and rationality.

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    Item Type: Preprint
    Additional Information: Forthcoming in Statistics and Probability Letters
    Keywords: Forecasting systems; Bayesianism
    Subjects: General Issues > Confirmation/Induction
    General Issues > Formal Learning Theory
    Specific Sciences > Probability/Statistics
    Depositing User: Gordon Belot
    Date Deposited: 20 Jun 2013 11:36
    Last Modified: 20 Jun 2013 11:36
    Item ID: 9842
    URI: http://philsci-archive.pitt.edu/id/eprint/9842

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