bayesm (version 1.1-2)

Scotch: Survey Data on Brands of Scotch Consumed

Description

from Simmons Survey. Brands used in last year for those respondents who report consuming scotch.

Usage

data(Scotch)

source

Edwards, Y. and G. Allenby (2003), "Multivariate Analysis of Multiple Response Data," JMR 40, 321-334.

References

Chapter 4, Bayesian Statistics and Marketing by Rossi et al. http://gsbwww.uchicago.edu/fac/peter.rossi/research/bsm.html

Examples

data(Scotch)
cat("Frequencies of Brands", fill=TRUE)
mat=apply(as.matrix(Scotch),2,mean)
print(mat)
##
## use Scotch data to run Multivariate Probit Model
##
if(nchar(Sys.getenv("LONG_TEST")) != 0){
##

y=as.matrix(Scotch)
p=ncol(y); n=nrow(y)
dimnames(y)=NULL
y=as.vector(t(y))
y=as.integer(y)
I_p=diag(p)
X=rep(I_p,n)
X=matrix(X,nrow=p)
X=t(X)

R=2000
Data=list(p=p,X=X,y=y)
Mcmc=list(R=R)
set.seed(66)
out=rmvpGibbs(Data=Data,Mcmc=Mcmc)

ind=(0:(p-1))*p + (1:p)
cat("Betadraws ",fill=TRUE)
mat=apply(out$betadraw/sqrt(out$sigmadraw[,ind]),2,quantile,probs=c(.01,.05,.5,.95,.99))
print(mat)
rdraw=matrix(double((R)*p*p),ncol=p*p)
rdraw=t(apply(out$sigmadraw,1,nmat))
cat("Draws of Correlation Matrix ",fill=TRUE)
mat=apply(rdraw,2,quantile,probs=c(.01,.05,.5,.95,.99))
## correlation matrix too large to print -- summarize
quantile(round(mat,digits=2))

}