EB.global {BAS} | R Documentation |
Finds the global Empirical Bayes estimates of g in Zellner's g-prior and model probabilities
EB.global.bma(object, tol= .1, g.0=NULL, max.iterations=100)
object |
A 'bma' object created by bas |
tol |
tolerance for estimating g |
g.0 |
intial value for g |
max.iterations |
Maximum number of iterations for the EM algorithm |
Uses the EM algorithm in Liang et al to estimate the type II MLE of g in Zellner's g prior
An object of class 'bma' using Zellner's g prior with an estimate of g based on all models
Merlise Clyde clyde@stat.duke.edu
Liang, F., Paulo, R., Molina, G., Clyde, M. and Berger,
J.O. (2005) Mixtures of g-priors for Bayesian Variable
Selection.
http://www.stat.duke.edu/05-12.pdf
## Not run: library(MASS) data(UScrime) UScrime[,-2] = log(UScrime[,-2]) # EB local uses a different g within each model crime.EBL = bas.lm(y ~ ., data=UScrime, n.models=2^15, prior="EB-local", initprobs= "eplogp") # use a common (global) estimate of g crime.EBG = EB.global.bma(crime.EBL) ## End(Not run)