| 1 | #' Generate a sample of (X,Y) of size n with default values |
| 2 | #' @param n sample size |
| 3 | #' @param p number of covariates |
| 4 | #' @param m size of the response |
| 5 | #' @param k number of clusters |
| 6 | #' @return list with X and Y |
| 7 | #' @export |
| 8 | #----------------------------------------------------------------------- |
| 9 | generateIOdefault = function(n, p, m, k) |
| 10 | { |
| 11 | covX = array(0, dim=c(p,p,k)) |
| 12 | covY = array(0, dim=c(m,m,k)) |
| 13 | for(r in 1:k) |
| 14 | { |
| 15 | covX[,,r] = diag(p) |
| 16 | covY[,,r] = diag(m) |
| 17 | } |
| 18 | |
| 19 | pi = rep(1./k,k) |
| 20 | |
| 21 | beta = array(0, dim=c(p,m,k)) |
| 22 | for(j in 1:p) |
| 23 | { |
| 24 | nonZeroCount = ceiling(m * runif(1)) |
| 25 | beta[j,1:nonZeroCount,] = matrix(runif(nonZeroCount*k), ncol=k) |
| 26 | } |
| 27 | |
| 28 | sample_IO = generateIO(covX, covY, pi, beta, n) |
| 29 | return (list(X=sample_IO$X,Y=sample_IO$Y)) |
| 30 | } |