# Jeffreys prior

## Summary

The Jeffreys prior is a kind of uninformative prior defined in terms of Fisher information, and motivated in terms of transformation invariance.

## Context

This concept has the prerequisites:

- Bayesian parameter estimation (The Jeffreys prior can be used in Bayesian parameter estimation.)
- uninformative priors (The Jeffreys prior is a kind of uninformative prior.)
- Fisher information (The Jeffreys prior is defined in terms of Fisher information.)

## Core resources (we're sorry, we haven't finished tracking down resources for this concept yet)

## Supplemental resources (the following are optional, but you may find them useful)

## -Paid-

→ Machine Learning: a Probabilistic Perspective

A very comprehensive graudate-level machine learning textbook.

Location:
Section 5.4.2, pages 166-168

## See also

-No Additional Notes-