+#' Generate a sample of (X,Y) of size n
+#' @param covX covariance for covariates (of size p*p*K)
+#' @param covY covariance for the response vector (of size m*m*K)
+#' @param pi proportion for each cluster
+#' @param beta regression matrix
+#' @param n sample size
+#'
+#' @return list with X and Y
+#' @export
+#-----------------------------------------------------------------------
generateIO = function(covX, covY, pi, beta, n)
{
- size_covX = dim(covX)
- p = size_covX[1]
- k = size_covX[3]
+ p = dim(covX)[1]
- size_covY = dim(covY)
- m = size_covY[1]
+ m = dim(covY)[1]
+ 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])
}
}