### sample from the multivariate normal distribution
rmvnorm<-function(n,mu,Sigma) 
{
  p<-length(mu)
  res<-matrix(0,nrow=n,ncol=p)
  if( n>0 & p>0 )
  {
    E<-matrix(rnorm(n*p),n,p)
    res<-t(  t(E%*%chol(Sigma)) +c(mu))
  }
  res
}
###


### sample from the Wishart distribution
rwish<-function(n,nu0,S0)
{
  sS0 <- chol(S0)
  S<-array( dim=c( dim(S0),n ) )
  for(i in 1:n)
  {
     Z <- matrix(rnorm(nu0 * dim(S0)[1]), nu0, dim(S0)[1]) %*% sS0
     S[,,i]<- t(Z)%*%Z
  }
  S[,,1:n]
}
###


### diabetes data
Y.reading<-dget("Y.reading")
Y.pima.miss<-dget("Y.pima.miss")
Y.pima.full<-dget("Y.pima.full")