-generateIOdefault = function(n, p, m, k){
- rangeX = 100
- meanX = rangeX*(1-matrix(runif(k*p),ncol = p))
-
- covX = array(0, dim=c(p,p,k))
- covY = array(0, dim=c(m,m,k))
-
- for(r in 1:k){
- covX[,,r] = diag(p)
- covY[,,r] = diag(m)
- }
-
- pi = (1/k) * rep(1,k)
-
- beta = array(0, dim=c(p,m,k))
-
- for(j in 1:p){
- nonZeroCount = ceiling(m * runif(1))
- beta[j,1:nonZeroCount,] = matrix(runif(nonZeroCount*k),ncol = k)
- }
-
- generate = generateIO(meanX, covX, covY, pi, beta, n)
-
- return(list(generate[[1]],generate[[2]]))
-}
\ No newline at end of file
+#' Generate a sample of (X,Y) of size n with default values
+#' @param n sample size
+#' @param p number of covariates
+#' @param m size of the response
+#' @param k number of clusters
+#' @return list with X and Y
+#' @export
+#-----------------------------------------------------------------------
+generateIOdefault = function(n, p, m, k)
+{
+ covX = diag(p)
+ covY = array(0, dim=c(m,m,k))
+ for(r in 1:k)
+ {
+ covY[,,r] = diag(m)
+ }
+
+ pi = rep(1./k,k)
+
+ beta = array(0, dim=c(p,m,k))
+ for(j in 1:p)
+ {
+ nonZeroCount = ceiling(m * runif(1))
+ beta[j,1:nonZeroCount,] = matrix(runif(nonZeroCount*k), ncol=k)
+ }
+
+ sample_IO = generateIO(covX, covY, pi, beta, n)
+ return (list(X=sample_IO$X,Y=sample_IO$Y))
+}