Scotch {bayesm} | R Documentation |
from Simmons Survey. Brands used in last year for those respondents who report consuming scotch.
data(Scotch)
A data frame with 2218 observations on the following 21 variables. All variables are coded 1 if consumed in last year, 0 if not.
Chivas.Regal
Dewar.s.White.Label
Johnnie.Walker.Black.Label
J...B
Johnnie.Walker.Red.Label
Other.Brands
Glenlivet
Cutty.Sark
Glenfiddich
Pinch..Haig.
Clan.MacGregor
Ballantine
Macallan
Passport
Black...White
Scoresby.Rare
Grants
Ushers
White.Horse
Knockando
the.Singleton
Edwards, Y. and G. Allenby (2003), "Multivariate Analysis of Multiple Response Data," JMR 40, 321-334.
Chapter 4, Bayesian Statistics and Marketing by Rossi et al.
http://faculty.chicagogsb.edu/peter.rossi/research/bsm.html
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(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)) attributes(mat)$class="bayesm.mat" summary(mat) rdraw=matrix(double((R)*p*p),ncol=p*p) rdraw=t(apply(out$sigmadraw,1,nmat)) attributes(rdraw)$class="bayesm.var" cat(" Draws of Correlation Matrix ",fill=TRUE) summary(rdraw) }