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     require(mvtnorm)
  20     X = rmvnorm(n, mean = rep(0,p), sigma = covX)
  21
  22     require(MASS) #simulate from a multivariate normal distribution
  23     for (i in 1:n)
  24     {
  25
  26         for (r in 1:k)
  27         {
  28             BXir = rep(0,m)
  29             for (mm in 1:m)
  30                 BXir[mm] = X[i,] %*% beta[,mm,r]
  31             Y[i,] = Y[i,] + pi[r] * mvrnorm(1,BXir, covY[,,r])
  32         }
  33     }
  34
  35     return (list(X=X,Y=Y))
  36 }