Jeffreys prior

Summary

The Jeffreys prior is a prior distribution whose density is proportional to the square root of the determinant of the Fisher information. Its defining property is invariance: it gives the same prior no matter how the parameter is written. It is a standard choice of a non-informative prior in Bayesian inference, and it is often improper.