diff --git a/R/boruta.R b/R/boruta.R
index 066de45..a765f14 100644
--- a/R/boruta.R
+++ b/R/boruta.R
@@ -88,9 +88,13 @@ boruta <- function(model,
     )
   
   # TODO: Parallelize the first five runs.
+  end_time <- NULL
   for (runNo in 1:maxRuns) {
+    start_time <- Sys.time()
     if (verbose) {
-      message(paste("Beginning Run", runNo))
+      time_info <- ""
+      if (!is.null(end_time)) time_info <- paste0("Last run took", (end_time-start_time)) 
+        message(paste("Beginning Run", runNo," ",time_info))
     }
     
     # stage 1 - create shadow features
@@ -133,9 +137,9 @@ boruta <- function(model,
     # Compute shadow stats
     shadow_importances <- agvim[names(agvim) %in% shadow_names]
     impHistory[runNo, "shadowMax"] <-
-      max_shadow_importance <- max(shadow_importances)
-    impHistory[runNo, "shadowMin"] <- min(shadow_importances)
-    impHistory[runNo, "shadowMean"] <- mean(shadow_importances)
+      max_shadow_importance <- max(shadow_importances, na.rm=TRUE)
+    impHistory[runNo, "shadowMin"] <- min(shadow_importances, na.rm=TRUE)
+    impHistory[runNo, "shadowMean"] <- mean(shadow_importances, na.rm=TRUE)
     agvim_filtered <- agvim[!(names(agvim) %in% shadow_names)]
     impHistory[runNo, names(agvim_filtered)] <- agvim_filtered
     
@@ -172,6 +176,8 @@ boruta <- function(model,
       break
     }
     
+    end_time <- Sys.time()
+    
   }
   
   vim$importance <- colMeans(impHistory, na.rm = TRUE)
@@ -201,14 +207,21 @@ plot.boruta = function(vim, type = 0, ...) {
     dplyr::left_join(data.frame(decisionList),
                      by = dplyr::join_by("name" == "predictor")) |>
     dplyr::mutate(decision =
-                    case_when(is.na(decision) ~ "Shadow", .default = decision)) |>
+                    dplyr::case_when(is.na(decision) ~ "Shadow", .default = decision)) |>
     dplyr::group_by(name) |>
     dplyr::mutate(median_value = median(value, na.rm = TRUE))
   
   if (type == 0) {
+    
+    # sort Inf values to the left
+    #impHistory[is.na(impHistory$median_value)] <- -Inf
+    impHistory$sort_value <- impHistory$median_value
+  #  mv <- min(impHistory$sort_value,na.rm=TRUE)
+   # impHistory$sort_value[impHistory$decision=="Rejected"]<- (mv-1)
+    
     ggplot2::ggplot(impHistory,
                     ggplot2::aes(
-                      x = stats::reorder(name, median_value),
+                      x = stats::reorder(name, sort_value),
                       y = value,
                       color = decision
                     )) +
@@ -216,7 +229,7 @@ plot.boruta = function(vim, type = 0, ...) {
       ggplot2::xlab("") +
       ggplot2::ylab("Importance") +
       ggplot2::scale_color_discrete(name = "Decision") +
-      ggplot2::theme(axis.text.x = element_text(angle = 45, hjust = 1))
+      ggplot2::theme(axis.text.x = ggplot2::element_text(angle = 45, hjust = 1))
   } else if (type == 1) {
     ggplot2::ggplot(impHistory,
                     ggplot2::aes(
@@ -226,7 +239,7 @@ plot.boruta = function(vim, type = 0, ...) {
                       col = name
                     )) +
       ggplot2::geom_line() +
-      ggplot2::geom_hline(aes(yintercept = median_value, col = name), lwd =
+      ggplot2::geom_hline(ggplot2::aes(yintercept = median_value, col = name), lwd =
                             2) +
       ggplot2::xlab("Round") +
       ggplot2::ylab("Importance") +