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.
Read more about Jeffreys Prior: Attributes, Minimum Description Length, Examples
Famous quotes containing the word prior:
“As humans have a prior right to existence over dogs by virtue of being more highly evolved and having a superior consciousness, so women have a prior right to existence over men. The elimination of any male is, therefore, a righteous and good act, an act highly beneficial to women as well as an act of mercy.”
—Valerie Solanas (b. 1940)