Date of this Version
IMS Collections: Borrowing Strength: Theory Powering Applications - A. Festschrift for Lawrence D. Brown
For the general Bayesian model uncertainty framework, the focus of this paper is on the development of model space priors which can compensate for redundancy between model classes, the so-called dilution priors proposed in George (1999). Several distinct approaches for dilution prior construction are suggested. One is based on tessellation determined neighborhoods, another on collinearity adjustments, and a third on pairwise distances between models.
The original and published work is available at: https://projecteuclid.org/euclid.imsc/1288099018#abstract
Model averaging, model selection, objective Bayes, prior distribution, variable selection
George, E. I. (2010). Dilution Priors: Compensating for Model Space Redundancy. IMS Collections: Borrowing Strength: Theory Powering Applications - A. Festschrift for Lawrence D. Brown, 6 158-165. http://dx.doi.org/10.1214/10-IMSCOLL611
Date Posted: 27 November 2017
This document has been peer reviewed.