diff --git a/R-package/R/predict.xgb.Booster.R b/R-package/R/predict.xgb.Booster.R
index 87666a55f..390ac689e 100644
--- a/R-package/R/predict.xgb.Booster.R
+++ b/R-package/R/predict.xgb.Booster.R
@@ -12,7 +12,7 @@ setClass("xgb.Booster")
 #'   untransformed margin value. In logistic regression, outputmargin=T will
 #'   output value before logistic transformation.
 #' @param ntreelimit limit number of trees used in prediction, this parameter is only valid for gbtree, but not for gblinear.
-#'   set it to be value bigger than 0
+#'   set it to be value bigger than 0. It will use all trees by default.
 #' @examples
 #' data(iris)
 #' bst <- xgboost(as.matrix(iris[,1:4]),as.numeric(iris[,5]), nrounds = 2)
@@ -28,7 +28,7 @@ setMethod("predict", signature = "xgb.Booster",
     ntreelimit <- 0
   } else {
     if (ntreelimit < 1){
-      stop("predict: ntreelimit must be greater equal than 1")
+      stop("predict: ntreelimit must be equal to or greater than 1")
     }
   }
   ret <- .Call("XGBoosterPredict_R", object, newdata, as.integer(outputmargin), as.integer(ntreelimit), PACKAGE = "xgboost")
diff --git a/R-package/man/predict-xgb.Booster-method.Rd b/R-package/man/predict-xgb.Booster-method.Rd
index d43fd7362..d192997d2 100644
--- a/R-package/man/predict-xgb.Booster-method.Rd
+++ b/R-package/man/predict-xgb.Booster-method.Rd
@@ -4,7 +4,8 @@
 \alias{predict,xgb.Booster-method}
 \title{Predict method for eXtreme Gradient Boosting model}
 \usage{
-\S4method{predict}{xgb.Booster}(object, newdata, outputmargin = FALSE)
+\S4method{predict}{xgb.Booster}(object, newdata, outputmargin = FALSE,
+  ntreelimit = NULL)
 }
 \arguments{
 \item{object}{Object of class "xgb.Boost"}
@@ -13,9 +14,12 @@
 \code{xgb.DMatrix}.}
 
 \item{outputmargin}{whether the prediction should be shown in the original
-  value of sum of functions, when outputmargin=TRUE, the prediction is
-  untransformed margin value. In logistic regression, outputmargin=T will
-  output value before logistic transformation.}
+value of sum of functions, when outputmargin=TRUE, the prediction is
+untransformed margin value. In logistic regression, outputmargin=T will
+output value before logistic transformation.}
+
+\item{ntreelimit}{limit number of trees used in prediction, this parameter is only valid for gbtree, but not for gblinear.
+set it to be value bigger than 0. It will use all trees by default.}
 }
 \description{
 Predicted values based on xgboost model object.
diff --git a/src/utils/omp.h b/src/utils/omp.h
index 43d01a54f..5eb5612e0 100644
--- a/src/utils/omp.h
+++ b/src/utils/omp.h
@@ -10,7 +10,7 @@
 #else
 #ifndef DISABLE_OPENMP
 // use pragma message instead of warning
-#pragma message ("Warning: OpenMP is not available. XGBoost will be compiled with single thread mode. You may want to use compiler with OpenMP support to get benefit of multi-threading.")
+#pragma message ("Warning: OpenMP is not available, xgboost will be compiled into single-thread code. Use OpenMP-enabled compiler to get benefit of multi-threading")
 #endif
 inline int omp_get_thread_num() { return 0; }
 inline int omp_get_num_threads() { return 1; }