diff --git a/R/singular_values.R b/R/singular_values.R
index 9e38ab9..747ebed 100644
--- a/R/singular_values.R
+++ b/R/singular_values.R
@@ -48,6 +48,8 @@ source("R/graphon_distribution.R")
 #'   which is about `1.5e‑8` on most platforms – small enough to be negligible
 #'   for most computations. If it is null, then it is not used. 
 #'   The guard is used for the value k = 0, which can cause arithmetic errors.
+#' @param scaled Rescales the matrix according to the dimension with the factor
+#' 1 / sqrt(n). Default value is FALSE.
 #'
 #' @return A numeric matrix **Q** of dimension `K × n`.  The \eqn{j}-th row
 #'         (for `j = 1,…,K`) contains the increments of the CDF evaluated at
@@ -105,7 +107,8 @@ compute_matrix <- function(
     sample_X_fn,
     fv,
     Fv,
-    guard = sqrt(.Machine$double.eps)
+    guard = sqrt(.Machine$double.eps),
+    scaled = FALSE
 ) {
   ## 1.1 Check inputs ==========================================================
   if (!is.numeric(seed) || length(seed) != 1) stop("'seed' must be a single number")
@@ -147,6 +150,7 @@ compute_matrix <- function(
   cdf_mat <- Fv(outer(graphon_quantiles, inner_products, "-")) # (K +1) x n matrix
   Q <- diff(cdf_mat, lag=1)                           # operates along rows
   
+  if (scaled) { Q <- 1 / sqrt(n) * Q }
   Q
 }