diff --git a/CVE/R/CVE.R b/CVE/R/CVE.R
index 1fcd4bf..6dc36d9 100644
--- a/CVE/R/CVE.R
+++ b/CVE/R/CVE.R
@@ -123,10 +123,10 @@
 #' #     y = f(B'x) + err
 #' # with f(x1, x2) = x1^2 + 2 * x2 and err ~ N(0, 0.25^2)
 #' y <- (x %*% b1)^2 + 2 * (x %*% b2) + 0.25 * rnorm(100)
-#' # calculate cve with method 'simple' for k unknown in 1, ..., 4
-#' cve.obj.s <- cve(y ~ x, max.dim = 4) # default method 'simple'
+#' # calculate cve with method 'mean' for k unknown in 1, ..., 4
+#' cve.obj.s <- cve(y ~ x, max.dim = 4) # default method 'mean'
 #' # calculate cve with method 'weighed' for k = 2
-#' cve.obj.w <- cve(y ~ x, k = 2, method = 'weighted')
+#' cve.obj.w <- cve(y ~ x, k = 2, method = 'weighted.mean')
 #' # estimate dimension from cve.obj.s
 #' khat <- predict_dim(cve.obj.s)$k
 #' # get cve-estimate for B with dimensions (p, k = khat)
@@ -145,13 +145,13 @@
 #' # projection matrix on span(B)
 #' # same as B %*% t(B) since B is semi-orthogonal
 #' PB <- B %*% solve(t(B) %*% B) %*% t(B)
-#' # cve estimates for B with simple and weighted method
+#' # cve estimates for B with mean and weighted method
 #' B.s <- coef(cve.obj.s, k = 2)
 #' B.w <- coef(cve.obj.w, k = 2)
 #' # same as B.s %*% t(B.s) since B.s is semi-orthogonal (same vor B.w)
 #' PB.s <- B.s %*% solve(t(B.s) %*% B.s) %*% t(B.s)
 #' PB.w <- B.w %*% solve(t(B.w) %*% B.w) %*% t(B.w)
-#' # compare estimation accuracy of simple and weighted cve estimate by
+#' # compare estimation accuracy of mean and weighted cve estimate by
 #' # Frobenius norm of difference of projections.
 #' norm(PB - PB.s, type = 'F')
 #' norm(PB - PB.w, type = 'F')
diff --git a/CVE/R/directions.R b/CVE/R/directions.R
index b74f2bc..73e9bbd 100644
--- a/CVE/R/directions.R
+++ b/CVE/R/directions.R
@@ -26,11 +26,11 @@ directions <- function(object, k, ...) {
 #' #    y = f(B'x) + err
 #' # with f(x1) = x1 and err ~ N(0, 0.25^2)
 #' y <- x %*% B + 0.25 * rnorm(100)
-#' # calculate cve with method 'simple' for k = 1
+#' # calculate cve with method 'mean' for k = 1
 #' set.seed(21)
-#' cve.obj.simple <- cve(y ~ x, k = 1, method = 'simple')
+#' cve.obj.mean <- cve(y ~ x, k = 1, method = 'mean')
 #' # get projected data for k = 1
-#' x.proj <- directions(cve.obj.simple, k = 1)
+#' x.proj <- directions(cve.obj.mean, k = 1)
 #' # plot y against projected data
 #' plot(x.proj, y)
 #'
diff --git a/CVE/man/cve.Rd b/CVE/man/cve.Rd
index 1b4fd42..6817b0f 100644
--- a/CVE/man/cve.Rd
+++ b/CVE/man/cve.Rd
@@ -109,7 +109,7 @@ y <- (x \%*\% b1)^2 + 2 * (x \%*\% b2) + 0.25 * rnorm(100)
 # calculate cve with method 'simple' for k unknown in 1, ..., 4
 cve.obj.s <- cve(y ~ x, max.dim = 4) # default method 'simple'
 # calculate cve with method 'weighed' for k = 2
-cve.obj.w <- cve(y ~ x, k = 2, method = 'weighted')
+cve.obj.w <- cve(y ~ x, k = 2, method = 'weighted.mean')
 # estimate dimension from cve.obj.s
 khat <- predict_dim(cve.obj.s)$k
 # get cve-estimate for B with dimensions (p, k = khat)
diff --git a/CVE/man/directions.cve.Rd b/CVE/man/directions.cve.Rd
index 630dd9d..87cd022 100644
--- a/CVE/man/directions.cve.Rd
+++ b/CVE/man/directions.cve.Rd
@@ -35,7 +35,7 @@ x <- matrix(rnorm(500), 100, 5)
 y <- x \%*\% B + 0.25 * rnorm(100)
 # calculate cve with method 'simple' for k = 1
 set.seed(21)
-cve.obj.simple <- cve(y ~ x, k = 1, method = 'simple')
+cve.obj.simple <- cve(y ~ x, k = 1, method = 'mean')
 # get projected data for k = 1
 x.proj <- directions(cve.obj.simple, k = 1)
 # plot y against projected data