Conditionality principle under unconstrained randomness

Vladimir Vovk

doi:10.1214/25-STS982

Conditionality principle under unconstrained randomness

Vladimir Vovk

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Abstract

A very simple example demonstrates that Fisher's application of the conditionality principle to regression ("fixed-x regression"), endorsed by David Sprott and many other followers, makes prediction impossible in the context of statistical learning theory. On the other hand, relaxing the requirement of conditionality makes it possible via, e.g., conformal prediction.

Original language	English
Pages (from-to)	218-221
Number of pages	4
Journal	Statistical Science
Volume	41
Issue number	1
Early online date	14 Jan 2026
DOIs	https://doi.org/10.1214/25-STS982
Publication status	Published - Feb 2026

Keywords

assumption of randomness
conditionality principle
machine learning
prediction
regression

Access to Document

10.1214/25-STS982

Accepted ManuscriptAccepted author manuscript, 109 KB

https://arxiv.org/abs/2402.04859

Cite this

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