B0653
Title: An objective prior from a scoring rule
Authors: Stephen Walker - University of Texas at Austin (United States)
Cristiano Villa - Newcastle University (United Kingdom) [presenting]
Abstract: A novel objective prior distribution levering on the connections between information, divergence and scoring rules, is introduced. In particular, we do so from the starting point of convex functions representing information in density functions. This provides a natural route to proper local scoring rules using Bregman divergence. Specifically, we determine the prior which solves setting the score function to be a constant. Although in itself this provides motivation for an objective prior, the prior also minimizes a corresponding information criterion.
