In Bayesian probability, the Jeffreys prior, named after Harold Jeffreys, is a non-informative (objective) prior distribution on parameter space that is proportional to the square root of the determinant of the Fisher information:
It has the key feature that it is invariant under reparameterization of the parameter vector . This makes it of special interest for use with scale parameters.
Famous quotes containing the word prior:
“Euphelia serves to grace my measure,
But Chloe is my real flame.”
—Matthew Prior (16641721)