R/generateIO.R

   1 #' Generate a sample of (X,Y) of size n
   2 #' @param covX covariance for covariates (of size p*p*K)
   3 #' @param covY covariance for the response vector (of size m*m*K)
   4 #' @param pi   proportion for each cluster
   5 #' @param beta regression matrix
   6 #' @param n    sample size
   7 #'
   8 #' @return list with X and Y
   9 #' @export
  10 #-----------------------------------------------------------------------
  11 generateIO = function(covX, covY, pi, beta, n)
  12 {
  13   p = dim(covX)[1]
  14
  15   m = dim(covY)[1]
  16   k = dim(covY)[3]
  17
  18   Y = matrix(0,n,m)
  19   BX = array(0, dim=c(n,m,k))
  20
  21   require(MASS) #simulate from a multivariate normal distribution
  22   for (i in 1:n)
  23   {
  24     for (r in 1:k)
  25     {
  26       BXir = rep(0,m)
  27       for (mm in 1:m)
  28         Bxir[[mm]] = X[i,] %*% beta[,mm,r]
  29       Y[i,] = Y[i,] + pi[r] * mvrnorm(1,BXir, covY[,,r])
  30     }
  31   }
  32
  33   return (list(X=X,Y=Y))
  34 }