# Comment on "Optimal prior for Bayesian inference in a constrained parameter space" by S. Hannestad and T. Tram, arXiv:1710.08899

## TL;DR

This paper clarifies that the Jeffreys prior remains unchanged when applied to constrained parameter spaces, countering previous claims that it differs from the unconstrained case.

## Contribution

It provides a correction to prior assertions, demonstrating that the Jeffreys prior is invariant under parameter constraints.

## Key findings

- Jeffreys prior is the same for constrained and unconstrained spaces
- Counter to previous claims, the prior remains unchanged under constraints
- Clarifies the correct application of Jeffreys prior in constrained Bayesian inference

## Abstract

The Jeffreys prior for a constrained part of a parameter space is the same as that for the unconstrained space, contrary to the assertions of Hannestad and Tram.