diff --git a/R-package/.Rbuildignore b/R-package/.Rbuildignore
index 6b3c4084e..b37d627ba 100644
--- a/R-package/.Rbuildignore
+++ b/R-package/.Rbuildignore
@@ -3,3 +3,4 @@
 \.dll$
 ^.*\.Rproj$
 ^\.Rproj\.user$
+README.md
diff --git a/R-package/DESCRIPTION b/R-package/DESCRIPTION
index c6975af5e..6f784fbb3 100644
--- a/R-package/DESCRIPTION
+++ b/R-package/DESCRIPTION
@@ -5,7 +5,7 @@ Version: 0.4-0
 Date: 2015-05-11
 Author: Tianqi Chen <tianqi.tchen@gmail.com>, Tong He <hetong007@gmail.com>, Michael Benesty <michael@benesty.fr>
 Maintainer: Tong He <hetong007@gmail.com>
-Description: Xgboost is short for eXtreme Gradient Boosting, which is an 
+Description: eXtreme Gradient Boosting, which is an 
     efficient and scalable implementation of gradient boosting framework. 
     This package is an R wrapper of xgboost. The package includes efficient 
     linear model solver and tree learning algorithms. The package can automatically 
diff --git a/R-package/R/utils.R b/R-package/R/utils.R
index f7f6b9192..e58601df8 100644
--- a/R-package/R/utils.R
+++ b/R-package/R/utils.R
@@ -288,7 +288,7 @@ xgb.cv.aggcv <- function(res, showsd = TRUE) {
     }
     ret <- paste(ret, sprintf("%f", mean(stats)), sep="")
     if (showsd) {
-      ret <- paste(ret, sprintf("+%f", sd(stats)), sep="")
+      ret <- paste(ret, sprintf("+%f", stats::sd(stats)), sep="")
     }
   }
   return (ret)
@@ -313,7 +313,7 @@ xgb.createFolds <- function(y, k = 10)
     if(cuts < 2) cuts <- 2
     if(cuts > 5) cuts <- 5
     y <- cut(y,
-             unique(quantile(y, probs = seq(0, 1, length = cuts))),
+             unique(stats::quantile(y, probs = seq(0, 1, length = cuts))),
              include.lowest = TRUE)
   }
 
diff --git a/R-package/R/xgb.cv.R b/R-package/R/xgb.cv.R
index 793d904cd..a5364db52 100644
--- a/R-package/R/xgb.cv.R
+++ b/R-package/R/xgb.cv.R
@@ -240,7 +240,7 @@ xgb.cv <- function(params=list(), data, nrounds, nfold, label = NULL, missing =
     else colnames <- colnamesMean
     
     type <- rep(x = "numeric", times = length(colnames))
-    dt <- read.table(text = "", colClasses = type, col.names = colnames) %>% as.data.table
+    dt <- utils::read.table(text = "", colClasses = type, col.names = colnames) %>% as.data.table
     split <- str_split(string = history, pattern = "\t")
     
     for(line in split) dt <- line[2:length(line)] %>% str_extract_all(pattern = "\\d*\\.+\\d*") %>% unlist %>% as.numeric %>% as.list %>% {rbindlist(list(dt, .), use.names = F, fill = F)}
diff --git a/R-package/R/xgb.plot.importance.R b/R-package/R/xgb.plot.importance.R
index eb0f8e346..b86d14323 100644
--- a/R-package/R/xgb.plot.importance.R
+++ b/R-package/R/xgb.plot.importance.R
@@ -33,7 +33,7 @@ xgb.plot.importance <- function(importance_matrix = NULL, numberOfClusters = c(1
   if (!"data.table" %in% class(importance_matrix))  {     
     stop("importance_matrix: Should be a data.table.")
   }
-  if (!require(ggplot2, quietly = TRUE)) {
+  if (!requireNamespace(ggplot2, quietly = TRUE)) {
     stop("ggplot2 package is required for plotting the importance", call. = FALSE)
   }
   if (!requireNamespace("Ckmeans.1d.dp", quietly = TRUE)) {
@@ -46,7 +46,7 @@ xgb.plot.importance <- function(importance_matrix = NULL, numberOfClusters = c(1
   clusters <- suppressWarnings(Ckmeans.1d.dp::Ckmeans.1d.dp(importance_matrix[,Gain], numberOfClusters))
   importance_matrix[,"Cluster":=clusters$cluster %>% as.character]
     
-  plot <- ggplot(importance_matrix, aes(x=reorder(Feature, Gain), y = Gain, width= 0.05), environment = environment())+  geom_bar(aes(fill=Cluster), stat="identity", position="identity") + coord_flip() + xlab("Features") + ylab("Gain") + ggtitle("Feature importance") + theme(plot.title = element_text(lineheight=.9, face="bold"), panel.grid.major.y = element_blank() )
+  plot <- ggplot(importance_matrix, aes(x=stats::reorder(Feature, Gain), y = Gain, width= 0.05), environment = environment())+  geom_bar(aes(fill=Cluster), stat="identity", position="identity") + coord_flip() + xlab("Features") + ylab("Gain") + ggtitle("Feature importance") + theme(plot.title = element_text(lineheight=.9, face="bold"), panel.grid.major.y = element_blank() )
   
   return(plot)  
 }