Lopez-Wild, Josiah (2026) Testing for Priors. [Preprint]

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Abstract

The Problem of the Priors can be stated as the following question: what norms, if any, motivate our choice of one prior over another? Subjective Bayesians argue that there is no problem: your beliefs are what they are, and there is no rational requirement beyond coherence. Nonetheless I argue that in common problems in Bayesian statistics, we are uncertain which prior best represents our beliefs. Using tools from algorithmic randomness I develop a prior determination method that guides agents to priors in a principled manner. I argue that the method produces priors that can all claim to represent the agent's credences. I then prove that the method is algorithmically implementable in principle, and the priors thus constructed enjoy nice merging properties.

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Item Type:	Preprint
Creators:	Creators Email ORCID Lopez-Wild, Josiah jlopezwi@uci.edu 0009-0000-4847-4481
Keywords:	Bayesian epistemology, prior, computability, algorithmic randomness
Subjects:	General Issues > Confirmation/Induction Specific Sciences > Probability/Statistics
Depositing User:	Mr. Josiah Lopez-Wild
Date Deposited:	13 Apr 2026 12:34
Last Modified:	13 Apr 2026 12:34
Item ID:	29039
Subjects:	General Issues > Confirmation/Induction Specific Sciences > Probability/Statistics
Date:	2026
URI:	https://philsci-archive.pitt.edu/id/eprint/29039

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