+++ /dev/null
-#' 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)
-{
- p = dim(covX)[1]
-
- m = dim(covY)[1]
- k = dim(covY)[3]
-
- Y = matrix(0,n,m)
- 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]
- Y[i,] = Y[i,] + pi[r] * mvrnorm(1,BXir, covY[,,r])
- }
- }
-
- return (list(X=X,Y=Y))
-}