rbprobitGibbs(bayesm) | R Documentation |
rbprobitGibbs
implements the Albert and Chib Gibbs Sampler for the binary probit model.
rbprobitGibbs(Data, Prior, Mcmc)
Data |
list(X,y) |
Prior |
list(betabar,A) |
Mcmc |
list(R,keep) |
Model: y = Xbeta + e. e ~ N(0,I). Prior: beta ~ N(betabar,A^-1).
List arguments contain
X
y
betabar
A
R
keep
betadraw |
R/keep x k array of betadraws |
Peter Rossi, Graduate School of Business, University of Chicago, Peter.Rossi@ChicagoGsb.edu.
For further discussion, see Bayesian Statistics and Marketing
by Allenby, McCulloch, and Rossi, Chapter 3.
http://gsbwww.uchicago.edu/fac/peter.rossi/research/bsm.html
## rbprobitGibbs example ## set.seed(66) simbprobit= function(X,beta) { ## function to simulate from binary probit including x variable y=ifelse((X%*%beta+rnorm(nrow(X)))<0,0,1) list(X=X,y=y,beta=beta) } nobs=200 X=cbind(rep(1,nobs),runif(nobs),runif(nobs)) beta=c(0,1,-1) nvar=ncol(X) simout=simbprobit(X,beta) Data=list(X=simout$X,y=simout$y) Mcmc=list(R=2000,keep=1) out=rbprobitGibbs(Data=Data,Mcmc=Mcmc) cat(" Betadraws ",fill=TRUE) mat=apply(out$betadraw,2,quantile,probs=c(.01,.05,.5,.95,.99)) mat=rbind(beta,mat); rownames(mat)[1]="beta"; print(mat)