diff --git a/R/data.R b/R/data.R
index 98da5b51db8bad95f86187dd0e66353c48d1e5dc..589c801a33bd56cfb39b86b6b06ddb406cc5dbe4 100644
--- a/R/data.R
+++ b/R/data.R
@@ -38,9 +38,7 @@
 #' 
 #' @examples 
 #' data(truffles)
-#' \dontrun{
 #' summary(truffles)
 #' plot(1:15, rainfall[1, ], type = "l", xlab = "month", ylab = "rainfall (mm)")
-#' }
 
 NULL
\ No newline at end of file
diff --git a/R/ridgeSIR.R b/R/ridgeSIR.R
index a0b3acc76ff572312d85e55a199d5b9d790d9021..a05be30fedd0610e6acd3229b7fb59e5e51c7e38 100644
--- a/R/ridgeSIR.R
+++ b/R/ridgeSIR.R
@@ -46,7 +46,7 @@
 #' y <- log(abs(x %*% beta[ ,1])) + sqrt(abs(x %*% beta[ ,2]))
 #' y <- y + rnorm(50, sd = 0.1)
 #' res_ridge <- ridgeSIR(x, y, H = 10, d = 2, mu2 = 10^8)
-#' \dontrun{print(res_ridge)}
+#' res_ridge
 #' 
 #' @return S3 object of class \code{ridgeRes}: a list consisting of
 #' \describe{
@@ -245,9 +245,9 @@ print.ridgeRes <- function(x, ...) {
 #' listH <- c(5, 10)
 #' list_d <- 1:4
 #' set.seed(1129)
-#' \dontrun{
-#' res_tune <- tune.ridgeSIR(x, y, listH, list_mu2, list_d, 
-#'                           nfolds = 10, parallel = TRUE)}
+#' \donttest{
+#' res_tune <- tune.ridgeSIR(x, y, listH, list_mu2, list_d, nfolds = 10, 
+#'                           parallel = TRUE, ncores = 2)}
 #' 
 #' @return a data frame with tested parameters and corresponding CV error and 
 #' estimation of R(d)
@@ -285,7 +285,7 @@ tune.ridgeSIR <- function(x, y, listH, list_mu2, list_d, nfolds = 10,
       mu2 <- list_mu2[ind_mu2]
       res_SIR <- processSIR(pre, max_d, mu2)
       global_projector[[ind_mu2]] <- sapply(list_d, function(d) {
-        projectorEDR(res_SIR$EDR[ ,1:d,drop = FALSE], pre$ccov_x, mu2)
+        projectorEDR(res_SIR$EDR[ , 1:d, drop = FALSE], pre$ccov_x, mu2)
       }, simplify = FALSE)
     }
     
diff --git a/R/sfcb_methods.R b/R/sfcb_methods.R
index 25a28b4d708b23e5600982562b4365fe0b244ba8..ae39684ba51d672a39ad167e511541675c23d5f3 100644
--- a/R/sfcb_methods.R
+++ b/R/sfcb_methods.R
@@ -66,11 +66,9 @@
 #'              summary.method = "pls", selection.method = "relief")
 #' summary(out1)
 #' 
-#' \dontrun{
 #' plot(out1)
 #' plot(out1, plot.type = "selection")
 #' plot(out1, plot.type = "importance")
-#' }
 #' 
 #' out2 <- sfcb(rainfall, truffles, group.method = "adjclust", 
 #'              summary.method = "basics", selection.method = "none",
diff --git a/R/sparseSIR.R b/R/sparseSIR.R
index 7eb9bf7503af9c2b03618092f53e9b6324ce5e62..ed41152743d81ac9f5e9c82f32d1725e304e9f1a 100644
--- a/R/sparseSIR.R
+++ b/R/sparseSIR.R
@@ -90,6 +90,7 @@ sparseSIR <- function(object, inter_len, adaptive = FALSE, sel_prop = 0.05,
                       parallel = FALSE, ncores = NULL) {
   if (parallel) {
     if (is.null(ncores)) ncores <- min(detectCores() - 1)
+    print(ncores)
     registerDoParallel(cores = ncores)
   }
   oldwarn <- getOption("warn")
@@ -259,7 +260,7 @@ print.sparseRes <- function(x, ...) {
 #' beta[((tsteps < 0.6) | (tsteps > 0.75)), 2] <- 0
 #' y <- log(abs(x %*% beta[ ,1]) + 1) + sqrt(abs(x %*% beta[ ,2]))
 #' y <- y + rnorm(nsim, sd = 0.1)
-#' \dontrun{
+#' \donttest{
 #' res_ridge <- ridgeSIR(x, y, H = 10, d = 2)
 #' res_sparse <- sparseSIR(res_ridge, rep(1, ncol(x)))
 #' proj_data <- project(res_sparse)
@@ -334,7 +335,8 @@ project <- function(object) {
 #' y <- log(abs(x %*% beta[ ,1]) + 1) + sqrt(abs(x %*% beta[ ,2]))
 #' y <- y + rnorm(nsim, sd = 0.1)
 #' res_ridge <- ridgeSIR(x, y, H = 10, d = 2, mu2 = 10^8)
-#' \dontrun{res_fused <- SISIR(res_ridge, rep(1, ncol(x)))}
+#' \donttest{res_fused <- SISIR(res_ridge, rep(1, ncol(x)), ncores = 2)
+#' res_fused}
 #' 
 #' @return S3 object of class \code{SISIR}: a list consisting of
 #' \describe{
diff --git a/man/SFCB-class.Rd b/man/SFCB-class.Rd
index 4a6902d848ab461c6fb791118b2a87a986c62948..2612081a19ead240f242da20f9667e06d394c233 100644
--- a/man/SFCB-class.Rd
+++ b/man/SFCB-class.Rd
@@ -90,11 +90,9 @@ out1 <- sfcb(rainfall, truffles, group.method = "adjclust",
              summary.method = "pls", selection.method = "relief")
 summary(out1)
 
-\dontrun{
 plot(out1)
 plot(out1, plot.type = "selection")
 plot(out1, plot.type = "importance")
-}
 
 out2 <- sfcb(rainfall, truffles, group.method = "adjclust", 
              summary.method = "basics", selection.method = "none",
diff --git a/man/SISIR.Rd b/man/SISIR.Rd
index 42f32349ec5d5a397240589d2e073964e6071ad2..bd15b59386502580fd65179410da09dfa20053c9 100644
--- a/man/SISIR.Rd
+++ b/man/SISIR.Rd
@@ -74,7 +74,8 @@ beta[((tsteps < 0.6) | (tsteps > 0.75)), 2] <- 0
 y <- log(abs(x \%*\% beta[ ,1]) + 1) + sqrt(abs(x \%*\% beta[ ,2]))
 y <- y + rnorm(nsim, sd = 0.1)
 res_ridge <- ridgeSIR(x, y, H = 10, d = 2, mu2 = 10^8)
-\dontrun{res_fused <- SISIR(res_ridge, rep(1, ncol(x)))}
+\donttest{res_fused <- SISIR(res_ridge, rep(1, ncol(x)), ncores = 2)
+res_fused}
 
 }
 \references{
diff --git a/man/project.Rd b/man/project.Rd
index bdf51090acbafed0541baf6e5285d5a62e30c22c..621087c9ae0c1be9b00938510697faab46b67cb3 100644
--- a/man/project.Rd
+++ b/man/project.Rd
@@ -36,7 +36,7 @@ beta[((tsteps < 0.2) | (tsteps > 0.5)), 1] <- 0
 beta[((tsteps < 0.6) | (tsteps > 0.75)), 2] <- 0
 y <- log(abs(x \%*\% beta[ ,1]) + 1) + sqrt(abs(x \%*\% beta[ ,2]))
 y <- y + rnorm(nsim, sd = 0.1)
-\dontrun{
+\donttest{
 res_ridge <- ridgeSIR(x, y, H = 10, d = 2)
 res_sparse <- sparseSIR(res_ridge, rep(1, ncol(x)))
 proj_data <- project(res_sparse)
diff --git a/man/ridgeSIR.Rd b/man/ridgeSIR.Rd
index 248061b73f786eba99a0067a956c33d13c4ddee9..22759679e832868654373854fea817d553613e7b 100644
--- a/man/ridgeSIR.Rd
+++ b/man/ridgeSIR.Rd
@@ -56,7 +56,7 @@ beta <- cbind(sin(tsteps*3*pi/2), sin(tsteps*5*pi/2))
 y <- log(abs(x \%*\% beta[ ,1])) + sqrt(abs(x \%*\% beta[ ,2]))
 y <- y + rnorm(50, sd = 0.1)
 res_ridge <- ridgeSIR(x, y, H = 10, d = 2, mu2 = 10^8)
-\dontrun{print(res_ridge)}
+res_ridge
 
 }
 \references{
diff --git a/man/truffles.Rd b/man/truffles.Rd
index 2763f3073ad56197deb5fc4e5cd3005fb30107a3..2fde4e8d1d868d9008d43c47d891c882c8e048fe 100644
--- a/man/truffles.Rd
+++ b/man/truffles.Rd
@@ -32,11 +32,9 @@ station) and truffle production data are courtesy of the truffle patch.
 }
 \examples{
 data(truffles)
-\dontrun{
 summary(truffles)
 plot(1:15, rainfall[1, ], type = "l", xlab = "month", ylab = "rainfall (mm)")
 }
-}
 \references{
 Baragatti M., Grollemund P.M., Montpied P., Dupouey J.L., Gravier J., Murat 
 C., Le Tacon F. (2019) Influence of annual climatic variations, climate
diff --git a/man/tune.ridgeSIR.Rd b/man/tune.ridgeSIR.Rd
index 85ccd2cef9aa8e16c05409c5aa2be999e75623c9..dd83c9352646fb296f0dd9f7cd1196aa78c158d9 100644
--- a/man/tune.ridgeSIR.Rd
+++ b/man/tune.ridgeSIR.Rd
@@ -55,9 +55,9 @@ list_mu2 <- 10^(0:10)
 listH <- c(5, 10)
 list_d <- 1:4
 set.seed(1129)
-\dontrun{
-res_tune <- tune.ridgeSIR(x, y, listH, list_mu2, list_d, 
-                          nfolds = 10, parallel = TRUE)}
+\donttest{
+res_tune <- tune.ridgeSIR(x, y, listH, list_mu2, list_d, nfolds = 10, 
+                          parallel = TRUE, ncores = 2)}
 
 }
 \references{