X-Git-Url: https://git.auder.net/?p=valse.git;a=blobdiff_plain;f=R%2FgenerateIOdefault.R;h=85213cc9e5e4536a60b159b02bcb61dbfb1f1e07;hp=fc01cd811850073cf04498706d7cc5a465a0f9bd;hb=d1531659214edd6eaef0ac9ec835455614bba16c;hpb=6bd2e869a17f3980d52820643c1c1b5f3725738e

diff --git a/R/generateIOdefault.R b/R/generateIOdefault.R
index fc01cd8..85213cc 100644
--- a/R/generateIOdefault.R
+++ b/R/generateIOdefault.R
@@ -1,22 +1,30 @@
+#' 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 = 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 = 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))
+  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 = 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))
 }