G-prior

In statistics, the g-prior is an objective prior for the regression coefficients of a multiple regression. It was introduced by Arnold Zellner.[1] It is a key tool in Bayes and empirical Bayes variable selection.[2][3]

  1. ^ Zellner, A. (1986). "On Assessing Prior Distributions and Bayesian Regression Analysis with g Prior Distributions". In Goel, P.; Zellner, A. (eds.). Bayesian Inference and Decision Techniques: Essays in Honor of Bruno de Finetti. Studies in Bayesian Econometrics and Statistics. Vol. 6. New York: Elsevier. pp. 233–243. ISBN 978-0-444-87712-3.
  2. ^ George, E.; Foster, D. P. (2000). "Calibration and empirical Bayes variable selection". Biometrika. 87 (4): 731–747. CiteSeerX 10.1.1.18.3731. doi:10.1093/biomet/87.4.731.
  3. ^ Liang, F.; Paulo, R.; Molina, G.; Clyde, M. A.; Berger, J. O. (2008). "Mixtures of g priors for Bayesian variable selection". Journal of the American Statistical Association. 103 (481): 410–423. CiteSeerX 10.1.1.206.235. doi:10.1198/016214507000001337.