replace \dontrun with \donttest

R/adjust_significance_level.R

@@ -29,7 +29,7 @@
 #' # ...
 #' 
 #' # Simulation-based adjustment of the significance level using `allocation_rule`
-#' \dontrun{
+#' \donttest{
 #' adjusted_alpha <- adjust_significance_level(
 #'   allocation_rule, models,
 #'   N_total = 150, N_ini = rep(10, 5), N_block = 10,

R/learn_allocation_rule.R

@@ -65,7 +65,7 @@
 #' 
 #' # We obtain an optimal adaptive allocation rule by executing 
 #' # `learn_allocation_rule()` with the `models`.
-#' \dontrun{
+#' \donttest{
 #' allocation_rule <- learn_allocation_rule(
 #'   models,
 #'   N_total = 150, N_ini = rep(10, 5), N_block = 10, Delta = 1.3,
@@ -85,7 +85,7 @@
 #' )
 #' 
 #' # Then, we specify the argument `rl_models` in `learn_allocation_rule` function.
-#' \dontrun{
+#' \donttest{
 #' allocation_rule <- learn_allocation_rule(
 #'   models,
 #'   N_total = 150, N_ini = rep(10, 5), N_block = 10, Delta = 1.3,

R/rl_config_set.R

@@ -27,14 +27,14 @@
 #' @return A list of reinforcement learning configuration parameters
 #' 
 #' @examples
-#' \dontrun{
+#' \donttest{
 #' allocation_rule <- learn_allocation_rule(
 #'   models, 
 #'   N_total = 150, N_ini = rep(10, 5), N_block = 10, Delta = 1.3,
 #'   outcome_type = "continuous", sd_normal = sqrt(4.5), 
 #'   seed = 123, 
-#'   # We change `iter` to 200 and `cores` for reinforcement learning to 8
-#'   rl_config = rl_config_set(iter = 200, cores = 8), 
+#'   # We change `iter` to 200 and `cores` for reinforcement learning to 2
+#'   rl_config = rl_config_set(iter = 200, cores = 2), 
 #'   alpha = 0.025
 #' )
 #' } 

R/rl_dnn_config.R

@@ -14,7 +14,7 @@
 #' @return A list of DNN configuration parameters
 #' 
 #' @examples
-#' \dontrun{
+#' \donttest{
 #' allocation_rule <- learn_allocation_rule(
 #'   models, 
 #'   N_total = 150, N_ini = rep(10, 5), N_block = 10, Delta = 1.3,

R/simulate_one_trial.R

@@ -37,7 +37,7 @@
 #'        the estimated target dose, and the MAE.
 #' 
 #' @examples
-#' \dontrun{  
+#' \donttest{  
 #' # We computed `allocation_rule` and `adjusted_alpha`
 #' # ...
 #'