k = dim(covY)[3]
Y = matrix(0,n,m)
- BX = array(0, dim=c(n,m,k))
+ require(mvtnorm)
+ X = rmvnorm(n, mean = rep(0,p), sigma = covX)
require(MASS) #simulate from a multivariate normal distribution
for (i in 1:n)
{
+
for (r in 1:k)
{
BXir = rep(0,m)
for (mm in 1:m)
- Bxir[[mm]] = X[i,] %*% beta[,mm,r]
+ BXir[mm] = X[i,] %*% beta[,mm,r]
Y[i,] = Y[i,] + pi[r] * mvrnorm(1,BXir, covY[,,r])
}
}