Response to: "A note on conditional densities, Bayes' rule, and recent criticisms of Bayesian inference" by Yan et al., 2026
Klaus Mosegaard, Andrew Curtis

TL;DR
This paper refutes claims that the use of conditional expectations resolves physical inconsistencies in Bayesian methods, emphasizing that their critique does not address the core issue of physical versus statistical consistency.
Contribution
It clarifies the distinction between physical and statistical consistency in Bayesian inference and refutes Yan et al.'s claims of mathematical errors and resolution of physical inconsistency.
Findings
Conditional expectations do not resolve physical inconsistency in Bayesian methods.
Yan et al.'s critique contains mathematical errors.
The original preprint's conclusions remain valid.
Abstract
In a recent preprint (Mosegaard and Curtis, 2024, arXiv:2411.13570v2) we analyzed the consequences of ignoring the well-known inconsistency of classical conditional probability densities. We explained how this inconsistency, together with acausality in hierarchical methods, invalidate a variety of commonly applied Bayesian methods when applied to problems in the physical world. Yan et al., 2026, (arXiv:2603.27038v1) published a note, in which they claim, contrary to our preprint, that there are no inconsistencies if one uses the method of conditional expectations to derive probabilities. Furthermore, they believe that there are mathematical errors in our exposition and in our use of the Bayesian framework. This note is a response to the claims made by Yan et al. Yan et al. do not discriminate between physical and statistical consistency. Their note addresses statistical consistency of a…
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