BAS (version 0.85)

EB.global: Finds the global Empirical Bayes estimates for BMA

Description

Finds the global Empirical Bayes estimates of g in Zellner's g-prior and model probabilities

Usage

EB.global.bma(object, tol= .1, g.0=NULL, max.iterations=100)

Arguments

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

Value

• An object of class 'bma' using Zellner's g prior with an estimate of g based on all models

Details

Uses the EM algorithm in Liang et al to estimate the type II MLE of g in Zellner's g prior

References

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

See Also

bas, update

Examples

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)