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: z = Xβ + e. e ~ N(0,I). y=1, if z> 0.
Prior: β ~ 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 Rossi, Allenby and McCulloch, Chapter 3.
http://faculty.chicagogsb.edu/peter.rossi/research/bsm.html
## ## rbprobitGibbs example ## if(nchar(Sys.getenv("LONG_TEST")) != 0) {R=2000} else {R=10} 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) Data1=list(X=simout$X,y=simout$y) Mcmc1=list(R=R,keep=1) out=rbprobitGibbs(Data=Data1,Mcmc=Mcmc1) summary(out$betadraw,tvalues=beta) if(0){ ## plotting example plot(out$betadraw,tvalues=beta) }