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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
Creators:
CreatorsEmailORCID
Belot, Gordon
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 15:36
Last Modified: 20 Jun 2013 15:36
Item ID: 9842
Subjects: General Issues > Confirmation/Induction
General Issues > Formal Learning Theory
Specific Sciences > Probability/Statistics
Date: 19 June 2013
URI: https://philsci-archive-dev.library.pitt.edu/id/eprint/9842

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