diff --git a/NAMESPACE b/NAMESPACE
index bc55060..76e1d65 100644
--- a/NAMESPACE
+++ b/NAMESPACE
@@ -3,6 +3,7 @@
 S3method(plot,theta)
 S3method(print,theta)
 S3method(summary,theta)
+export(EMAlgorithm)
 export(SimulateGMCMData)
 export(SimulateGMMData)
 export(Uhat)
@@ -24,6 +25,7 @@ importFrom(graphics,contour)
 importFrom(graphics,lines)
 importFrom(graphics,points)
 importFrom(stats,approxfun)
+importFrom(stats,cov)
 importFrom(stats,cov.wt)
 importFrom(stats,cov2cor)
 importFrom(stats,kmeans)
diff --git a/R/EMAlgortihm.R b/R/EMAlgortihm.R
index f304216..e80195e 100644
--- a/R/EMAlgortihm.R
+++ b/R/EMAlgortihm.R
@@ -30,11 +30,19 @@
 #'                 \code{x[i, ]} is realized from the \code{j}'th component.}
 #' @author Anders Ellern Bilgrau <anders.ellern.bilgrau@@gmail.com>
 #' @seealso \code{\link{rtheta}}, \code{\link{PseudoEMAlgorithm}}
+#' @importFrom stats cov
 #' @examples
+#' set.seed(3)
+#' true.theta <- rtheta(d = 2, m = 3, method = "old")
+#' true.theta$sigma <- lapply(true.theta$sigma, cov2cor) # Scale
+#' \dontrun{
+#' plot(true.theta, nlevels = 20, add.ellipses = TRUE)
+#' }
 #'
-#' set.seed(10)
-#' data <- SimulateGMCMData(n = 1000, d = 2, m = 3)
+#' data <- SimulateGMCMData(n = 1000, theta = true.theta)
 #' start.theta <- rtheta(d = 2, m = 3)
+#' start.theta$mu <- t(kmeans(data$z, 3)$centers) # More sensible location estimates
+#' start.theta <- as.theta(start.theta) # Coerce the matrix to a list
 #' res <- GMCM:::EMAlgorithm(data$z, theta = start.theta)
 #'
 #' par(mfrow = c(1,2))
@@ -42,9 +50,9 @@
 #'      col = rainbow(3)[data$K])
 #' plot(data$z, cex = 0.5, pch = 16, main = "GMM clustering",
 #'      col = rainbow(3)[apply(res$kappa,1,which.max)])
-#'
-EMAlgorithm <- function (x, theta, m, eps = 1e-6, max.ite = 1e5,
-                         trace.theta = FALSE, verbose = FALSE) {
+#'@export
+EMAlgorithm <- function(x, theta, m, eps = 1e-6, max.ite = 1e5,
+                        trace.theta = FALSE, verbose = FALSE) {
   if (missing(m) && missing(theta)) {
     stop("Either m or theta should be provided.")
   }
diff --git a/inst/NEWS.Rd b/inst/NEWS.Rd
index 552b5d2..10cccf0 100644
--- a/inst/NEWS.Rd
+++ b/inst/NEWS.Rd
@@ -5,8 +5,11 @@
 
 \section{Changes in version 1.3.1 (2018-MM-DD)}{
   \itemize{
+    \item By request, \code{EMAlgorithm} is now exported to the user interface.
+      A better example is also provided.
     \item Minor improvements to documentation.
   }
+}
 
 \section{Changes in version 1.3 (2018-12-05)}{
   \itemize{
diff --git a/man/EMAlgorithm.Rd b/man/EMAlgorithm.Rd
index 3067fab..ed3621f 100644
--- a/man/EMAlgorithm.Rd
+++ b/man/EMAlgorithm.Rd
@@ -47,10 +47,17 @@ to \code{Mclust} in the \code{mclust}-package. If \code{theta} is not given,
 a k-means clustering is used to determine the initial \code{theta}.
 }
 \examples{
+set.seed(3)
+true.theta <- rtheta(d = 2, m = 3, method = "old")
+true.theta$sigma <- lapply(true.theta$sigma, cov2cor) # Scale
+\dontrun{
+plot(true.theta, nlevels = 20, add.ellipses = TRUE)
+}
 
-set.seed(10)
-data <- SimulateGMCMData(n = 1000, d = 2, m = 3)
+data <- SimulateGMCMData(n = 1000, theta = true.theta)
 start.theta <- rtheta(d = 2, m = 3)
+start.theta$mu <- t(kmeans(data$z, 3)$centers) # More sensible location estimates
+start.theta <- as.theta(start.theta) # Coerce the matrix to a list
 res <- GMCM:::EMAlgorithm(data$z, theta = start.theta)
 
 par(mfrow = c(1,2))
@@ -58,7 +65,6 @@ plot(data$z, cex = 0.5, pch = 16, main = "Simulated data",
      col = rainbow(3)[data$K])
 plot(data$z, cex = 0.5, pch = 16, main = "GMM clustering",
      col = rainbow(3)[apply(res$kappa,1,which.max)])
-
 }
 \seealso{
 \code{\link{rtheta}}, \code{\link{PseudoEMAlgorithm}}