diff --git a/R-package/NAMESPACE b/R-package/NAMESPACE
index 3cd80d5c2..dd788ca2f 100644
--- a/R-package/NAMESPACE
+++ b/R-package/NAMESPACE
@@ -1,6 +1,16 @@
 # Generated by roxygen2: do not edit by hand
 
+S3method("[",xgb.DMatrix)
+S3method("dimnames<-",xgb.DMatrix)
+S3method(dim,xgb.DMatrix)
+S3method(dimnames,xgb.DMatrix)
+S3method(getinfo,xgb.DMatrix)
+S3method(predict,xgb.Booster)
+S3method(predict,xgb.Booster.handle)
+S3method(setinfo,xgb.DMatrix)
+S3method(slice,xgb.DMatrix)
 export(getinfo)
+export(print.xgb.DMatrix)
 export(setinfo)
 export(slice)
 export(xgb.DMatrix)
@@ -19,8 +29,6 @@ export(xgb.save)
 export(xgb.save.raw)
 export(xgb.train)
 export(xgboost)
-exportMethods(nrow)
-exportMethods(predict)
 import(methods)
 importClassesFrom(Matrix,dgCMatrix)
 importClassesFrom(Matrix,dgeMatrix)
diff --git a/R-package/R/getinfo.xgb.DMatrix.R b/R-package/R/getinfo.xgb.DMatrix.R
deleted file mode 100644
index 3000a1e7d..000000000
--- a/R-package/R/getinfo.xgb.DMatrix.R
+++ /dev/null
@@ -1,55 +0,0 @@
-setClass('xgb.DMatrix')
-
-#' Get information of an xgb.DMatrix object
-#' 
-#' Get information of an xgb.DMatrix object
-#' 
-#' The information can be one of the following:
-#' 
-#' \itemize{
-#'     \item \code{label}: label Xgboost learn from ;
-#'     \item \code{weight}: to do a weight rescale ;
-#'     \item \code{base_margin}: base margin is the base prediction Xgboost will boost from ;
-#'     \item \code{nrow}: number of rows of the \code{xgb.DMatrix}.
-#' }
-#' 
-#' @examples
-#' data(agaricus.train, package='xgboost')
-#' train <- agaricus.train
-#' dtrain <- xgb.DMatrix(train$data, label=train$label)
-#' labels <- getinfo(dtrain, 'label')
-#' setinfo(dtrain, 'label', 1-labels)
-#' labels2 <- getinfo(dtrain, 'label')
-#' stopifnot(all(labels2 == 1-labels))
-#' @rdname getinfo
-#' @export
-getinfo <- function(object, ...){
-    UseMethod("getinfo")
-}
-
-
-
-#' @param object Object of class \code{xgb.DMatrix}
-#' @param name the name of the field to get
-#' @param ... other parameters
-#' @rdname getinfo
-#' @method getinfo xgb.DMatrix
-setMethod("getinfo", signature = "xgb.DMatrix",
-          definition = function(object, name) {
-              if (typeof(name) != "character") {
-                  stop("xgb.getinfo: name must be character")
-              }
-              if (class(object) != "xgb.DMatrix") {
-                  stop("xgb.setinfo: first argument dtrain must be xgb.DMatrix")
-              }
-              if (name != "label" && name != "weight" &&
-                      name != "base_margin" && name != "nrow") {
-                  stop(paste("xgb.getinfo: unknown info name", name))
-              }
-              if (name != "nrow"){
-                  ret <- .Call("XGDMatrixGetInfo_R", object, name, PACKAGE = "xgboost")
-              } else {
-                  ret <- xgb.numrow(object)
-              }
-              return(ret)
-          })
diff --git a/R-package/R/nrow.xgb.DMatrix.R b/R-package/R/nrow.xgb.DMatrix.R
deleted file mode 100644
index 9ea039764..000000000
--- a/R-package/R/nrow.xgb.DMatrix.R
+++ /dev/null
@@ -1,19 +0,0 @@
-setGeneric("nrow")
-
-#' @title Number of xgb.DMatrix rows
-#' @description \code{nrow} return the number of rows present in the \code{xgb.DMatrix}.
-#' @param x Object of class \code{xgb.DMatrix}
-#' 
-#' @examples
-#' data(agaricus.train, package='xgboost')
-#' train <- agaricus.train
-#' dtrain <- xgb.DMatrix(train$data, label=train$label)
-#' stopifnot(nrow(dtrain) == nrow(train$data))
-#' 
-#' @export
-setMethod("nrow",
-          signature = "xgb.DMatrix",
-          definition = function(x) {
-            xgb.numrow(x)
-          }
-)
diff --git a/R-package/R/predict.xgb.Booster.handle.R b/R-package/R/predict.xgb.Booster.handle.R
deleted file mode 100644
index 3e4013b75..000000000
--- a/R-package/R/predict.xgb.Booster.handle.R
+++ /dev/null
@@ -1,18 +0,0 @@
-#' Predict method for eXtreme Gradient Boosting model handle
-#' 
-#' Predicted values based on xgb.Booster.handle object.
-#' 
-#' @param object Object of class "xgb.Boost.handle"
-#' @param ... Parameters pass to \code{predict.xgb.Booster}
-#' 
-setMethod("predict", signature = "xgb.Booster.handle",
-          definition = function(object, ...) {
-  if (class(object) != "xgb.Booster.handle"){
-    stop("predict: model in prediction must be of class xgb.Booster.handle")
-  }
-
-  bst <- xgb.handleToBooster(object)
-
-  ret <- predict(bst, ...)
-  return(ret)
-})
diff --git a/R-package/R/setinfo.xgb.DMatrix.R b/R-package/R/setinfo.xgb.DMatrix.R
deleted file mode 100644
index 427de08d4..000000000
--- a/R-package/R/setinfo.xgb.DMatrix.R
+++ /dev/null
@@ -1,37 +0,0 @@
-#' Set information of an xgb.DMatrix object
-#' 
-#' Set information of an xgb.DMatrix object
-#' 
-#' It can be one of the following:
-#' 
-#' \itemize{
-#'     \item \code{label}: label Xgboost learn from ;
-#'     \item \code{weight}: to do a weight rescale ;
-#'     \item \code{base_margin}: base margin is the base prediction Xgboost will boost from ;
-#'     \item \code{group}.
-#' }
-#' 
-#' @examples
-#' data(agaricus.train, package='xgboost')
-#' train <- agaricus.train
-#' dtrain <- xgb.DMatrix(train$data, label=train$label)
-#' labels <- getinfo(dtrain, 'label')
-#' setinfo(dtrain, 'label', 1-labels)
-#' labels2 <- getinfo(dtrain, 'label')
-#' stopifnot(all(labels2 == 1-labels))
-#' @rdname setinfo
-#' @export
-setinfo <- function(object, ...){
-  UseMethod("setinfo")
-}
-
-#' @param object Object of class "xgb.DMatrix"
-#' @param name the name of the field to get
-#' @param info the specific field of information to set
-#' @param ... other parameters
-#' @rdname setinfo
-#' @method setinfo xgb.DMatrix
-setMethod("setinfo", signature = "xgb.DMatrix",
-          definition = function(object, name, info) {
-            xgb.setinfo(object, name, info)
-          })
diff --git a/R-package/R/slice.xgb.DMatrix.R b/R-package/R/slice.xgb.DMatrix.R
deleted file mode 100644
index 4626c2b4d..000000000
--- a/R-package/R/slice.xgb.DMatrix.R
+++ /dev/null
@@ -1,44 +0,0 @@
-setClass('xgb.DMatrix')
-
-#' Get a new DMatrix containing the specified rows of
-#' orginal xgb.DMatrix object
-#'
-#' Get a new DMatrix containing the specified rows of
-#' orginal xgb.DMatrix object
-#' 
-#' @examples
-#' data(agaricus.train, package='xgboost')
-#' train <- agaricus.train
-#' dtrain <- xgb.DMatrix(train$data, label=train$label)
-#' dsub <- slice(dtrain, 1:3)
-#' @rdname slice
-#' @export
-slice <- function(object, ...){
-    UseMethod("slice")
-}
-
-#' @param object Object of class "xgb.DMatrix"
-#' @param idxset a integer vector of indices of rows needed
-#' @param ... other parameters
-#' @rdname slice
-#' @method slice xgb.DMatrix
-setMethod("slice", signature = "xgb.DMatrix",
-          definition = function(object, idxset, ...) {
-              if (class(object) != "xgb.DMatrix") {
-                  stop("slice: first argument dtrain must be xgb.DMatrix")
-              }
-              ret <- .Call("XGDMatrixSliceDMatrix_R", object, idxset,
-                           PACKAGE = "xgboost")
-
-              attr_list <- attributes(object)
-              nr <- xgb.numrow(object)
-              len <- sapply(attr_list,length)
-              ind <- which(len == nr)
-              if (length(ind) > 0) {
-                  nms <- names(attr_list)[ind]
-                  for (i in 1:length(ind)) {
-                    attr(ret,nms[i]) <- attr(object,nms[i])[idxset]
-                  }
-              }
-              return(structure(ret, class = "xgb.DMatrix"))
-          })
diff --git a/R-package/R/utils.R b/R-package/R/utils.R
index 926e82994..514826b3c 100644
--- a/R-package/R/utils.R
+++ b/R-package/R/utils.R
@@ -1,4 +1,4 @@
-  #' @importClassesFrom Matrix dgCMatrix dgeMatrix
+#' @importClassesFrom Matrix dgCMatrix dgeMatrix
 #' @import methods
 
 # depends on matrix
@@ -9,131 +9,10 @@
   library.dynam.unload("xgboost", libpath)
 }
 
-# set information into dmatrix, this mutate dmatrix
-xgb.setinfo <- function(dmat, name, info) {
-  if (class(dmat) != "xgb.DMatrix") {
-    stop("xgb.setinfo: first argument dtrain must be xgb.DMatrix")
-  }
-  if (name == "label") {
-    if (length(info) != xgb.numrow(dmat))
-      stop("The length of labels must equal to the number of rows in the input data")
-    .Call("XGDMatrixSetInfo_R", dmat, name, as.numeric(info),
-          PACKAGE = "xgboost")
-    return(TRUE)
-  }
-  if (name == "weight") {
-    if (length(info) != xgb.numrow(dmat))
-      stop("The length of weights must equal to the number of rows in the input data")
-    .Call("XGDMatrixSetInfo_R", dmat, name, as.numeric(info),
-          PACKAGE = "xgboost")
-    return(TRUE)
-  }
-  if (name == "base_margin") {
-    # if (length(info)!=xgb.numrow(dmat))
-    #   stop("The length of base margin must equal to the number of rows in the input data")
-    .Call("XGDMatrixSetInfo_R", dmat, name, as.numeric(info),
-          PACKAGE = "xgboost")
-    return(TRUE)
-  }
-  if (name == "group") {
-    if (sum(info) != xgb.numrow(dmat))
-      stop("The sum of groups must equal to the number of rows in the input data")
-    .Call("XGDMatrixSetInfo_R", dmat, name, as.integer(info),
-          PACKAGE = "xgboost")
-    return(TRUE)
-  }
-  stop(paste("xgb.setinfo: unknown info name", name))
-  return(FALSE)
-}
 
-# construct a Booster from cachelist
-xgb.Booster <- function(params = list(), cachelist = list(), modelfile = NULL) {
-  if (typeof(cachelist) != "list") {
-    stop("xgb.Booster: only accepts list of DMatrix as cachelist")
-  }
-  for (dm in cachelist) {
-    if (class(dm) != "xgb.DMatrix") {
-      stop("xgb.Booster: only accepts list of DMatrix as cachelist")
-    }
-  }
-  handle <- .Call("XGBoosterCreate_R", cachelist, PACKAGE = "xgboost")
-  if (length(params) != 0) {
-    for (i in 1:length(params)) {
-      p <- params[i]
-      .Call("XGBoosterSetParam_R", handle, gsub("\\.", "_", names(p)), as.character(p),
-            PACKAGE = "xgboost")
-    }
-  }
-  if (!is.null(modelfile)) {
-    if (typeof(modelfile) == "character") {
-      .Call("XGBoosterLoadModel_R", handle, modelfile, PACKAGE = "xgboost")
-    } else if (typeof(modelfile) == "raw") {
-      .Call("XGBoosterLoadModelFromRaw_R", handle, modelfile, PACKAGE = "xgboost")
-    } else {
-      stop("xgb.Booster: modelfile must be character or raw vector")
-    }
-  }
-  return(structure(handle, class = "xgb.Booster.handle"))
-}
-
-# convert xgb.Booster.handle to xgb.Booster
-xgb.handleToBooster <- function(handle, raw = NULL)
-{
-  bst <- list(handle = handle, raw = raw)
-  class(bst) <- "xgb.Booster"
-  return(bst)
-}
-
-# Check whether an xgb.Booster object is complete
-xgb.Booster.check <- function(bst, saveraw = TRUE)
-{
-  isnull <- is.null(bst$handle)
-  if (!isnull) {
-    isnull <- .Call("XGCheckNullPtr_R", bst$handle, PACKAGE="xgboost")
-  }
-  if (isnull) {
-    bst$handle <- xgb.Booster(modelfile = bst$raw)
-  } else {
-    if (is.null(bst$raw) && saveraw)
-      bst$raw <- xgb.save.raw(bst$handle)
-  }
-  return(bst)
-}
-
-## ----the following are low level iteratively function, not needed if
+## ----the following are low level iterative functions, not needed if
 ## you do not want to use them ---------------------------------------
-# get dmatrix from data, label
-xgb.get.DMatrix <- function(data, label = NULL, missing = NA, weight = NULL) {
-  inClass <- class(data)
-  if (inClass == "dgCMatrix" || inClass == "matrix") {
-    if (is.null(label)) {
-      stop("xgboost: need label when data is a matrix")
-    }
-    dtrain <- xgb.DMatrix(data, label = label, missing = missing)
-    if (!is.null(weight)){
-      xgb.setinfo(dtrain, "weight", weight)
-    }
-  } else {
-    if (!is.null(label)) {
-      warning("xgboost: label will be ignored.")
-    }
-    if (inClass == "character") {
-      dtrain <- xgb.DMatrix(data)
-    } else if (inClass == "xgb.DMatrix") {
-      dtrain <- data
-    } else if (inClass == "data.frame") {
-      stop("xgboost only support numerical matrix input,
-           use 'data.matrix' to transform the data.")
-    } else {
-      stop("xgboost: Invalid input of data")
-    }
-  }
-  return (dtrain)
-}
-xgb.numrow <- function(dmat) {
-  nrow <- .Call("XGDMatrixNumRow_R", dmat, PACKAGE="xgboost")
-  return(nrow)
-}
+
 # iteratively update booster with customized statistics
 xgb.iter.boost <- function(booster, dtrain, gpair) {
   if (class(booster) != "xgb.Booster.handle") {
@@ -227,7 +106,7 @@ xgb.cv.mknfold <- function(dall, nfold, param, stratified, folds) {
            "\tConsider providing pre-computed CV-folds through the folds parameter.")
     }
     y <- getinfo(dall, 'label')
-    randidx <- sample(1 : xgb.numrow(dall))
+    randidx <- sample(1 : nrow(dall))
     if (stratified & length(y) == length(randidx)) {
       y <- y[randidx]
       #
diff --git a/R-package/R/predict.xgb.Booster.R b/R-package/R/xgb.Booster.R
similarity index 54%
rename from R-package/R/predict.xgb.Booster.R
rename to R-package/R/xgb.Booster.R
index d608f3465..97f5ea37f 100644
--- a/R-package/R/predict.xgb.Booster.R
+++ b/R-package/R/xgb.Booster.R
@@ -1,13 +1,65 @@
-setClass("xgb.Booster.handle")
-setClass("xgb.Booster",
-         slots = c(handle = "xgb.Booster.handle",
-                   raw = "raw"))
+# Construct a Booster from cachelist
+# internal utility function
+xgb.Booster <- function(params = list(), cachelist = list(), modelfile = NULL) {
+  if (typeof(cachelist) != "list") {
+    stop("xgb.Booster: only accepts list of DMatrix as cachelist")
+  }
+  for (dm in cachelist) {
+    if (class(dm) != "xgb.DMatrix") {
+      stop("xgb.Booster: only accepts list of DMatrix as cachelist")
+    }
+  }
+  handle <- .Call("XGBoosterCreate_R", cachelist, PACKAGE = "xgboost")
+  if (length(params) != 0) {
+    for (i in 1:length(params)) {
+      p <- params[i]
+      .Call("XGBoosterSetParam_R", handle, gsub("\\.", "_", names(p)), as.character(p),
+            PACKAGE = "xgboost")
+    }
+  }
+  if (!is.null(modelfile)) {
+    if (typeof(modelfile) == "character") {
+      .Call("XGBoosterLoadModel_R", handle, modelfile, PACKAGE = "xgboost")
+    } else if (typeof(modelfile) == "raw") {
+      .Call("XGBoosterLoadModelFromRaw_R", handle, modelfile, PACKAGE = "xgboost")
+    } else {
+      stop("xgb.Booster: modelfile must be character or raw vector")
+    }
+  }
+  return(structure(handle, class = "xgb.Booster.handle"))
+}
+
+# Convert xgb.Booster.handle to xgb.Booster
+# internal utility function
+xgb.handleToBooster <- function(handle, raw = NULL)
+{
+  bst <- list(handle = handle, raw = raw)
+  class(bst) <- "xgb.Booster"
+  return(bst)
+}
+
+# Check whether an xgb.Booster object is complete
+# internal utility function
+xgb.Booster.check <- function(bst, saveraw = TRUE)
+{
+  isnull <- is.null(bst$handle)
+  if (!isnull) {
+    isnull <- .Call("XGCheckNullPtr_R", bst$handle, PACKAGE="xgboost")
+  }
+  if (isnull) {
+    bst$handle <- xgb.Booster(modelfile = bst$raw)
+  } else {
+    if (is.null(bst$raw) && saveraw)
+      bst$raw <- xgb.save.raw(bst$handle)
+  }
+  return(bst)
+}
 
 #' Predict method for eXtreme Gradient Boosting model
 #' 
-#' Predicted values based on xgboost model object.
+#' Predicted values based on either xgboost model or model handle object.
 #' 
-#' @param object Object of class "xgb.Boost"
+#' @param object Object of class \code{xgb.Booster} or \code{xgb.Booster.handle}
 #' @param newdata takes \code{matrix}, \code{dgCMatrix}, local data file or 
 #'   \code{xgb.DMatrix}. 
 #' @param missing Missing is only used when input is dense matrix, pick a float 
@@ -20,6 +72,7 @@ setClass("xgb.Booster",
 #'  only valid for gbtree, but not for gblinear. set it to be value bigger 
 #'  than 0. It will use all trees by default.
 #' @param predleaf whether predict leaf index instead. If set to TRUE, the output will be a matrix object.
+#' @param ... Parameters pass to \code{predict.xgb.Booster}
 #' 
 #' @details  
 #' The option \code{ntreelimit} purpose is to let the user train a model with lots 
@@ -36,13 +89,14 @@ setClass("xgb.Booster",
 #' data(agaricus.test, package='xgboost')
 #' train <- agaricus.train
 #' test <- agaricus.test
+#' 
 #' bst <- xgboost(data = train$data, label = train$label, max.depth = 2, 
 #'                eta = 1, nthread = 2, nround = 2,objective = "binary:logistic")
 #' pred <- predict(bst, test$data)
+#' @rdname predict.xgb.Booster
 #' @export
-setMethod("predict", signature = "xgb.Booster",
-          definition = function(object, newdata, missing = NA,
-                                outputmargin = FALSE, ntreelimit = NULL, predleaf = FALSE) {
+predict.xgb.Booster <- function(object, newdata, missing = NA,
+    outputmargin = FALSE, ntreelimit = NULL, predleaf = FALSE) {
   if (class(object) != "xgb.Booster"){
     stop("predict: model in prediction must be of class xgb.Booster")
   } else {
@@ -77,4 +131,14 @@ setMethod("predict", signature = "xgb.Booster",
       }
   }
   return(ret)
-})
+}
+
+#' @rdname predict.xgb.Booster
+#' @export
+predict.xgb.Booster.handle <- function(object, ...) {
+
+  bst <- xgb.handleToBooster(object)
+
+  ret <- predict(bst, ...)
+  return(ret)
+}
diff --git a/R-package/R/xgb.DMatrix.R b/R-package/R/xgb.DMatrix.R
index c34c65d95..c5f4fed72 100644
--- a/R-package/R/xgb.DMatrix.R
+++ b/R-package/R/xgb.DMatrix.R
@@ -1,9 +1,9 @@
 #' Contruct xgb.DMatrix object
 #' 
-#' Contruct xgb.DMatrix object from dense matrix, sparse matrix or local file.
+#' Contruct xgb.DMatrix object from dense matrix, sparse matrix 
+#' or local file (that was created previously by saving an \code{xgb.DMatrix}).
 #' 
-#' @param data a \code{matrix} object, a \code{dgCMatrix} object or a character 
-#'   indicating the data file.
+#' @param data a \code{matrix} object, a \code{dgCMatrix} object or a character representing a filename
 #' @param info a list of information of the xgb.DMatrix object
 #' @param missing Missing is only used when input is dense matrix, pick a float
 #'     value that represents missing value. Sometime a data use 0 or other extreme value to represents missing values.
@@ -18,27 +18,348 @@
 #' dtrain <- xgb.DMatrix('xgb.DMatrix.data')
 #' @export
 xgb.DMatrix <- function(data, info = list(), missing = NA, ...) {
+  cnames <- NULL
   if (typeof(data) == "character") {
     handle <- .Call("XGDMatrixCreateFromFile_R", data, as.integer(FALSE),
                     PACKAGE = "xgboost")
   } else if (is.matrix(data)) {
     handle <- .Call("XGDMatrixCreateFromMat_R", data, missing,
                     PACKAGE = "xgboost")
+    cnames <- colnames(data)
   } else if (class(data) == "dgCMatrix") {
     handle <- .Call("XGDMatrixCreateFromCSC_R", data@p, data@i, data@x,
                     PACKAGE = "xgboost")
+    cnames <- colnames(data)
   } else {
     stop(paste("xgb.DMatrix: does not support to construct from ",
                typeof(data)))
   }
-  dmat <- structure(handle, class = "xgb.DMatrix")
+  dmat <- handle
+  attributes(dmat) <- list(.Dimnames = list(NULL, cnames), class = "xgb.DMatrix")
+  #dmat <- list(handle = handle, colnames = cnames)
+  #attr(dmat, 'class') <- "xgb.DMatrix"
 
   info <- append(info, list(...))
   if (length(info) == 0)
     return(dmat)
   for (i in 1:length(info)) {
     p <- info[i]
-    xgb.setinfo(dmat, names(p), p[[1]])
+    setinfo(dmat, names(p), p[[1]])
   }
   return(dmat)
 }
+
+
+# get dmatrix from data, label
+# internal helper method
+xgb.get.DMatrix <- function(data, label = NULL, missing = NA, weight = NULL) {
+  inClass <- class(data)
+  if (inClass == "dgCMatrix" || inClass == "matrix") {
+    if (is.null(label)) {
+      stop("xgboost: need label when data is a matrix")
+    }
+    dtrain <- xgb.DMatrix(data, label = label, missing = missing)
+    if (!is.null(weight)){
+      setinfo(dtrain, "weight", weight)
+    }
+  } else {
+    if (!is.null(label)) {
+      warning("xgboost: label will be ignored.")
+    }
+    if (inClass == "character") {
+      dtrain <- xgb.DMatrix(data)
+    } else if (inClass == "xgb.DMatrix") {
+      dtrain <- data
+    } else if (inClass == "data.frame") {
+      stop("xgboost only support numerical matrix input,
+           use 'data.matrix' to transform the data.")
+    } else {
+      stop("xgboost: Invalid input of data")
+    }
+  }
+  return (dtrain)
+}
+
+
+#' Dimensions of xgb.DMatrix
+#' 
+#' Returns a vector of numbers of rows and of columns in an \code{xgb.DMatrix}.
+#' @param x Object of class \code{xgb.DMatrix}
+#' 
+#' @details
+#' Note: since \code{nrow} and \code{ncol} internally use \code{dim}, they can also 
+#' be directly used with an \code{xgb.DMatrix} object.
+#'
+#' @examples
+#' data(agaricus.train, package='xgboost')
+#' train <- agaricus.train
+#' dtrain <- xgb.DMatrix(train$data, label=train$label)
+#' 
+#' stopifnot(nrow(dtrain) == nrow(train$data))
+#' stopifnot(ncol(dtrain) == ncol(train$data))
+#' stopifnot(all(dim(dtrain) == dim(train$data)))
+#' 
+#' @export
+dim.xgb.DMatrix <- function(x) {
+  c(.Call("XGDMatrixNumRow_R", x, PACKAGE="xgboost"),
+    .Call("XGDMatrixNumCol_R", x, PACKAGE="xgboost"))
+}
+
+
+#' Handling of column names of \code{xgb.DMatrix}
+#' 
+#' Only column names are supported for \code{xgb.DMatrix}, thus setting of 
+#' row names would have no effect and returnten row names would be NULL.
+#' 
+#' @param x object of class \code{xgb.DMatrix}
+#' @param value a list of two elements: the first one is ignored
+#'        and the second one is column names 
+#' 
+#' @details
+#' Generic \code{dimnames} methods are used by \code{colnames}.
+#' Since row names are irrelevant, it is recommended to use \code{colnames} directly.
+#'
+#' @examples
+#' data(agaricus.train, package='xgboost')
+#' train <- agaricus.train
+#' dtrain <- xgb.DMatrix(train$data, label=train$label)
+#' dimnames(dtrain)
+#' colnames(dtrain)
+#' colnames(dtrain) <- make.names(1:ncol(train$data))
+#' print(dtrain, verbose=TRUE)
+#' 
+#' @rdname dimnames.xgb.DMatrix
+#' @export
+dimnames.xgb.DMatrix <- function(x) {
+  attr(x, '.Dimnames')
+}
+
+#' @rdname dimnames.xgb.DMatrix
+#' @export
+`dimnames<-.xgb.DMatrix` <- function(x, value) {
+  if (!is.list(value) || length(value) != 2L)
+    stop("invalid 'dimnames' given: must be a list of two elements")
+  if (!is.null(value[[1L]]))
+    stop("xgb.DMatrix does not have rownames")
+  if (is.null(value[[2]])) {
+    attr(x, '.Dimnames') <- NULL
+    return(x)
+  }
+  if (ncol(x) != length(value[[2]])) 
+    stop("can't assign ", length(value[[2]]), " colnames to a ", 
+         ncol(x), " column xgb.DMatrix")
+  attr(x, '.Dimnames') <- value
+  x
+}
+
+
+#' Get information of an xgb.DMatrix object
+#' 
+#' Get information of an xgb.DMatrix object
+#' @param object Object of class \code{xgb.DMatrix}
+#' @param name the name of the information field to get (see details)
+#' @param ... other parameters
+#' 
+#' @details
+#' The \code{name} field can be one of the following:
+#' 
+#' \itemize{
+#'     \item \code{label}: label Xgboost learn from ;
+#'     \item \code{weight}: to do a weight rescale ;
+#'     \item \code{base_margin}: base margin is the base prediction Xgboost will boost from ;
+#'     \item \code{nrow}: number of rows of the \code{xgb.DMatrix}.
+#' }
+#' 
+#' @examples
+#' data(agaricus.train, package='xgboost')
+#' train <- agaricus.train
+#' dtrain <- xgb.DMatrix(train$data, label=train$label)
+#' 
+#' labels <- getinfo(dtrain, 'label')
+#' setinfo(dtrain, 'label', 1-labels)
+#' 
+#' labels2 <- getinfo(dtrain, 'label')
+#' stopifnot(all(labels2 == 1-labels))
+#' @rdname getinfo
+#' @export
+getinfo <- function(object, ...) UseMethod("getinfo")
+
+#' @rdname getinfo
+#' @export
+getinfo.xgb.DMatrix <- function(object, name) {
+  if (typeof(name) != "character") {
+    stop("getinfo: name must be character")
+  }
+  if (name != "label" && name != "weight" &&
+      name != "base_margin" && name != "nrow") {
+    stop(paste("getinfo: unknown info name", name))
+  }
+  if (name != "nrow"){
+    ret <- .Call("XGDMatrixGetInfo_R", object, name, PACKAGE = "xgboost")
+  } else {
+    ret <- nrow(object)
+  }
+  return(ret)
+}
+
+
+#' Set information of an xgb.DMatrix object
+#' 
+#' Set information of an xgb.DMatrix object
+#' 
+#' @param object Object of class "xgb.DMatrix"
+#' @param name the name of the field to get
+#' @param info the specific field of information to set
+#' @param ... other parameters
+#' 
+#' @details
+#' The \code{name} field can be one of the following:
+#' 
+#' \itemize{
+#'     \item \code{label}: label Xgboost learn from ;
+#'     \item \code{weight}: to do a weight rescale ;
+#'     \item \code{base_margin}: base margin is the base prediction Xgboost will boost from ;
+#'     \item \code{group}.
+#' }
+#' 
+#' @examples
+#' data(agaricus.train, package='xgboost')
+#' train <- agaricus.train
+#' dtrain <- xgb.DMatrix(train$data, label=train$label)
+#' 
+#' labels <- getinfo(dtrain, 'label')
+#' setinfo(dtrain, 'label', 1-labels)
+#' labels2 <- getinfo(dtrain, 'label')
+#' stopifnot(all.equal(labels2, 1-labels))
+#' @rdname setinfo
+#' @export
+setinfo <- function(object, ...) UseMethod("setinfo")
+
+#' @rdname setinfo
+#' @export
+setinfo.xgb.DMatrix <- function(object, name, info) {
+  if (name == "label") {
+    if (length(info) != nrow(object))
+      stop("The length of labels must equal to the number of rows in the input data")
+    .Call("XGDMatrixSetInfo_R", object, name, as.numeric(info),
+          PACKAGE = "xgboost")
+    return(TRUE)
+  }
+  if (name == "weight") {
+    if (length(info) != nrow(object))
+      stop("The length of weights must equal to the number of rows in the input data")
+    .Call("XGDMatrixSetInfo_R", object, name, as.numeric(info),
+          PACKAGE = "xgboost")
+    return(TRUE)
+  }
+  if (name == "base_margin") {
+    # if (length(info)!=nrow(object))
+    #   stop("The length of base margin must equal to the number of rows in the input data")
+    .Call("XGDMatrixSetInfo_R", object, name, as.numeric(info),
+          PACKAGE = "xgboost")
+    return(TRUE)
+  }
+  if (name == "group") {
+    if (sum(info) != nrow(object))
+      stop("The sum of groups must equal to the number of rows in the input data")
+    .Call("XGDMatrixSetInfo_R", object, name, as.integer(info),
+          PACKAGE = "xgboost")
+    return(TRUE)
+  }
+  stop(paste("setinfo: unknown info name", name))
+  return(FALSE)
+}
+
+
+#' Get a new DMatrix containing the specified rows of
+#' orginal xgb.DMatrix object
+#'
+#' Get a new DMatrix containing the specified rows of
+#' orginal xgb.DMatrix object
+#' 
+#' @param object Object of class "xgb.DMatrix"
+#' @param idxset a integer vector of indices of rows needed
+#' @param colset currently not used (columns subsetting is not available)
+#' @param ... other parameters (currently not used)
+#' 
+#' @examples
+#' data(agaricus.train, package='xgboost')
+#' train <- agaricus.train
+#' dtrain <- xgb.DMatrix(train$data, label=train$label)
+#' 
+#' dsub <- slice(dtrain, 1:42)
+#' labels1 <- getinfo(dsub, 'label')
+#' dsub <- dtrain[1:42, ]
+#' labels2 <- getinfo(dsub, 'label')
+#' all.equal(labels1, labels2)
+#' 
+#' @rdname slice.xgb.DMatrix
+#' @export
+slice <- function(object, ...) UseMethod("slice")
+
+#' @rdname slice.xgb.DMatrix
+#' @export
+slice.xgb.DMatrix <- function(object, idxset, ...) {
+  if (class(object) != "xgb.DMatrix") {
+    stop("slice: first argument dtrain must be xgb.DMatrix")
+  }
+  ret <- .Call("XGDMatrixSliceDMatrix_R", object, idxset, PACKAGE = "xgboost")
+
+  attr_list <- attributes(object)
+  nr <- nrow(object)
+  len <- sapply(attr_list, length)
+  ind <- which(len == nr)
+  if (length(ind) > 0) {
+    nms <- names(attr_list)[ind]
+    for (i in 1:length(ind)) {
+      attr(ret, nms[i]) <- attr(object, nms[i])[idxset]
+    }
+  }
+  return(structure(ret, class = "xgb.DMatrix"))
+}
+
+#' @rdname slice.xgb.DMatrix
+#' @export
+`[.xgb.DMatrix` <- function(object, idxset, colset=NULL) {
+  slice(object, idxset)
+}
+
+
+#' Print xgb.DMatrix
+#' 
+#' Print information about xgb.DMatrix. 
+#' Currently it displays dimensions and presence of info-fields and colnames.
+#' 
+#' @param x an xgb.DMatrix object
+#' @param verbose whether to print colnames (when present)
+#' @param ... not currently used
+#' 
+#' @examples
+#' data(agaricus.train, package='xgboost')
+#' train <- agaricus.train
+#' dtrain <- xgb.DMatrix(train$data, label=train$label)
+#' 
+#' dtrain
+#' print(dtrain, verbose=TRUE)
+#' @export
+print.xgb.DMatrix <- function(x, verbose=FALSE, ...) {
+  cat('xgb.DMatrix  dim:', nrow(x), 'x', ncol(x), ' info: ')
+  infos <- c()
+  if(length(getinfo(x, 'label')) > 0) infos <- 'label'
+  if(length(getinfo(x, 'weight')) > 0) infos <- c(infos, 'weight')
+  if(length(getinfo(x, 'base_margin')) > 0) infos <- c(infos, 'base_margin')
+  if (length(infos) == 0) infos <- 'NA'
+  cat(infos)
+  cnames <- colnames(x)
+  cat('  colnames:')
+  if (verbose & !is.null(cnames)) {
+    cat("\n'")
+    cat(cnames, sep="','")
+    cat("'")
+  } else {
+    if (is.null(cnames)) cat(' no')
+    else cat(' yes')
+  }
+  cat("\n")
+  invisible(x)
+}
diff --git a/R-package/R/xgb.cv.R b/R-package/R/xgb.cv.R
index 7ad2e5c41..e3faf33a0 100644
--- a/R-package/R/xgb.cv.R
+++ b/R-package/R/xgb.cv.R
@@ -169,11 +169,11 @@ xgb.cv <- function(params=list(), data, nrounds, nfold, label = NULL, missing =
         num_class <- params[['num_class']]
         if (is.null(num_class))
             stop('must set num_class to use softmax')
-        predictValues <- matrix(0,xgb.numrow(dtrain),num_class)
+        predictValues <- matrix(0, nrow(dtrain), num_class)
         mat_pred <- TRUE
     }
     else
-        predictValues <- rep(0,xgb.numrow(dtrain))
+        predictValues <- rep(0, nrow(dtrain))
     history <- c()
     print.every.n <- max(as.integer(print.every.n), 1L)
     for (i in 1:nrounds) {
diff --git a/R-package/man/dim.xgb.DMatrix.Rd b/R-package/man/dim.xgb.DMatrix.Rd
new file mode 100644
index 000000000..168782dec
--- /dev/null
+++ b/R-package/man/dim.xgb.DMatrix.Rd
@@ -0,0 +1,29 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/xgb.DMatrix.R
+\name{dim.xgb.DMatrix}
+\alias{dim.xgb.DMatrix}
+\title{Dimensions of xgb.DMatrix}
+\usage{
+\method{dim}{xgb.DMatrix}(x)
+}
+\arguments{
+\item{x}{Object of class \code{xgb.DMatrix}}
+}
+\description{
+Returns a vector of numbers of rows and of columns in an \code{xgb.DMatrix}.
+}
+\details{
+Note: since \code{nrow} and \code{ncol} internally use \code{dim}, they can also 
+be directly used with an \code{xgb.DMatrix} object.
+}
+\examples{
+data(agaricus.train, package='xgboost')
+train <- agaricus.train
+dtrain <- xgb.DMatrix(train$data, label=train$label)
+
+stopifnot(nrow(dtrain) == nrow(train$data))
+stopifnot(ncol(dtrain) == ncol(train$data))
+stopifnot(all(dim(dtrain) == dim(train$data)))
+
+}
+
diff --git a/R-package/man/dimnames.xgb.DMatrix.Rd b/R-package/man/dimnames.xgb.DMatrix.Rd
new file mode 100644
index 000000000..0877f294b
--- /dev/null
+++ b/R-package/man/dimnames.xgb.DMatrix.Rd
@@ -0,0 +1,36 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/xgb.DMatrix.R
+\name{dimnames.xgb.DMatrix}
+\alias{dimnames.xgb.DMatrix}
+\alias{dimnames<-.xgb.DMatrix}
+\title{Handling of column names of \code{xgb.DMatrix}}
+\usage{
+\method{dimnames}{xgb.DMatrix}(x)
+
+\method{dimnames}{xgb.DMatrix}(x) <- value
+}
+\arguments{
+\item{x}{object of class \code{xgb.DMatrix}}
+
+\item{value}{a list of two elements: the first one is ignored
+and the second one is column names}
+}
+\description{
+Only column names are supported for \code{xgb.DMatrix}, thus setting of 
+row names would have no effect and returnten row names would be NULL.
+}
+\details{
+Generic \code{dimnames} methods are used by \code{colnames}.
+Since row names are irrelevant, it is recommended to use \code{colnames} directly.
+}
+\examples{
+data(agaricus.train, package='xgboost')
+train <- agaricus.train
+dtrain <- xgb.DMatrix(train$data, label=train$label)
+dimnames(dtrain)
+colnames(dtrain)
+colnames(dtrain) <- make.names(1:ncol(train$data))
+print(dtrain, verbose=TRUE)
+
+}
+
diff --git a/R-package/man/getinfo.Rd b/R-package/man/getinfo.Rd
index f8b4f6b99..108d7edf2 100644
--- a/R-package/man/getinfo.Rd
+++ b/R-package/man/getinfo.Rd
@@ -1,27 +1,26 @@
 % Generated by roxygen2: do not edit by hand
-% Please edit documentation in R/getinfo.xgb.DMatrix.R
-\docType{methods}
+% Please edit documentation in R/xgb.DMatrix.R
 \name{getinfo}
 \alias{getinfo}
-\alias{getinfo,xgb.DMatrix-method}
+\alias{getinfo.xgb.DMatrix}
 \title{Get information of an xgb.DMatrix object}
 \usage{
 getinfo(object, ...)
 
-\S4method{getinfo}{xgb.DMatrix}(object, name)
+\method{getinfo}{xgb.DMatrix}(object, name)
 }
 \arguments{
 \item{object}{Object of class \code{xgb.DMatrix}}
 
 \item{...}{other parameters}
 
-\item{name}{the name of the field to get}
+\item{name}{the name of the information field to get (see details)}
 }
 \description{
 Get information of an xgb.DMatrix object
 }
 \details{
-The information can be one of the following:
+The \code{name} field can be one of the following:
 
 \itemize{
     \item \code{label}: label Xgboost learn from ;
@@ -34,8 +33,10 @@ The information can be one of the following:
 data(agaricus.train, package='xgboost')
 train <- agaricus.train
 dtrain <- xgb.DMatrix(train$data, label=train$label)
+
 labels <- getinfo(dtrain, 'label')
 setinfo(dtrain, 'label', 1-labels)
+
 labels2 <- getinfo(dtrain, 'label')
 stopifnot(all(labels2 == 1-labels))
 }
diff --git a/R-package/man/nrow-xgb.DMatrix-method.Rd b/R-package/man/nrow-xgb.DMatrix-method.Rd
deleted file mode 100644
index 1fd52b9c1..000000000
--- a/R-package/man/nrow-xgb.DMatrix-method.Rd
+++ /dev/null
@@ -1,23 +0,0 @@
-% Generated by roxygen2: do not edit by hand
-% Please edit documentation in R/nrow.xgb.DMatrix.R
-\docType{methods}
-\name{nrow,xgb.DMatrix-method}
-\alias{nrow,xgb.DMatrix-method}
-\title{Number of xgb.DMatrix rows}
-\usage{
-\S4method{nrow}{xgb.DMatrix}(x)
-}
-\arguments{
-\item{x}{Object of class \code{xgb.DMatrix}}
-}
-\description{
-\code{nrow} return the number of rows present in the \code{xgb.DMatrix}.
-}
-\examples{
-data(agaricus.train, package='xgboost')
-train <- agaricus.train
-dtrain <- xgb.DMatrix(train$data, label=train$label)
-stopifnot(nrow(dtrain) == nrow(train$data))
-
-}
-
diff --git a/R-package/man/predict-xgb.Booster.handle-method.Rd b/R-package/man/predict-xgb.Booster.handle-method.Rd
deleted file mode 100644
index 34454e555..000000000
--- a/R-package/man/predict-xgb.Booster.handle-method.Rd
+++ /dev/null
@@ -1,18 +0,0 @@
-% Generated by roxygen2: do not edit by hand
-% Please edit documentation in R/predict.xgb.Booster.handle.R
-\docType{methods}
-\name{predict,xgb.Booster.handle-method}
-\alias{predict,xgb.Booster.handle-method}
-\title{Predict method for eXtreme Gradient Boosting model handle}
-\usage{
-\S4method{predict}{xgb.Booster.handle}(object, ...)
-}
-\arguments{
-\item{object}{Object of class "xgb.Boost.handle"}
-
-\item{...}{Parameters pass to \code{predict.xgb.Booster}}
-}
-\description{
-Predicted values based on xgb.Booster.handle object.
-}
-
diff --git a/R-package/man/predict-xgb.Booster-method.Rd b/R-package/man/predict.xgb.Booster.Rd
similarity index 80%
rename from R-package/man/predict-xgb.Booster-method.Rd
rename to R-package/man/predict.xgb.Booster.Rd
index 341ced8c6..504037937 100644
--- a/R-package/man/predict-xgb.Booster-method.Rd
+++ b/R-package/man/predict.xgb.Booster.Rd
@@ -1,15 +1,17 @@
 % Generated by roxygen2: do not edit by hand
-% Please edit documentation in R/predict.xgb.Booster.R
-\docType{methods}
-\name{predict,xgb.Booster-method}
-\alias{predict,xgb.Booster-method}
+% Please edit documentation in R/xgb.Booster.R
+\name{predict.xgb.Booster}
+\alias{predict.xgb.Booster}
+\alias{predict.xgb.Booster.handle}
 \title{Predict method for eXtreme Gradient Boosting model}
 \usage{
-\S4method{predict}{xgb.Booster}(object, newdata, missing = NA,
+\method{predict}{xgb.Booster}(object, newdata, missing = NA,
   outputmargin = FALSE, ntreelimit = NULL, predleaf = FALSE)
+
+\method{predict}{xgb.Booster.handle}(object, ...)
 }
 \arguments{
-\item{object}{Object of class "xgb.Boost"}
+\item{object}{Object of class \code{xgb.Booster} or \code{xgb.Booster.handle}}
 
 \item{newdata}{takes \code{matrix}, \code{dgCMatrix}, local data file or 
 \code{xgb.DMatrix}.}
@@ -27,9 +29,11 @@ only valid for gbtree, but not for gblinear. set it to be value bigger
 than 0. It will use all trees by default.}
 
 \item{predleaf}{whether predict leaf index instead. If set to TRUE, the output will be a matrix object.}
+
+\item{...}{Parameters pass to \code{predict.xgb.Booster}}
 }
 \description{
-Predicted values based on xgboost model object.
+Predicted values based on either xgboost model or model handle object.
 }
 \details{
 The option \code{ntreelimit} purpose is to let the user train a model with lots 
@@ -46,6 +50,7 @@ data(agaricus.train, package='xgboost')
 data(agaricus.test, package='xgboost')
 train <- agaricus.train
 test <- agaricus.test
+
 bst <- xgboost(data = train$data, label = train$label, max.depth = 2, 
                eta = 1, nthread = 2, nround = 2,objective = "binary:logistic")
 pred <- predict(bst, test$data)
diff --git a/R-package/man/print.xgb.DMatrix.Rd b/R-package/man/print.xgb.DMatrix.Rd
new file mode 100644
index 000000000..95837b9f4
--- /dev/null
+++ b/R-package/man/print.xgb.DMatrix.Rd
@@ -0,0 +1,28 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/xgb.DMatrix.R
+\name{print.xgb.DMatrix}
+\alias{print.xgb.DMatrix}
+\title{Print xgb.DMatrix}
+\usage{
+print.xgb.DMatrix(x, verbose = FALSE, ...)
+}
+\arguments{
+\item{x}{an xgb.DMatrix object}
+
+\item{verbose}{whether to print colnames (when present)}
+
+\item{...}{not currently used}
+}
+\description{
+Print information about xgb.DMatrix. 
+Currently it displays dimensions and presence of info-fields and colnames.
+}
+\examples{
+data(agaricus.train, package='xgboost')
+train <- agaricus.train
+dtrain <- xgb.DMatrix(train$data, label=train$label)
+
+dtrain
+print(dtrain, verbose=TRUE)
+}
+
diff --git a/R-package/man/setinfo.Rd b/R-package/man/setinfo.Rd
index cb939721e..b182a9042 100644
--- a/R-package/man/setinfo.Rd
+++ b/R-package/man/setinfo.Rd
@@ -1,14 +1,13 @@
 % Generated by roxygen2: do not edit by hand
-% Please edit documentation in R/setinfo.xgb.DMatrix.R
-\docType{methods}
+% Please edit documentation in R/xgb.DMatrix.R
 \name{setinfo}
 \alias{setinfo}
-\alias{setinfo,xgb.DMatrix-method}
+\alias{setinfo.xgb.DMatrix}
 \title{Set information of an xgb.DMatrix object}
 \usage{
 setinfo(object, ...)
 
-\S4method{setinfo}{xgb.DMatrix}(object, name, info)
+\method{setinfo}{xgb.DMatrix}(object, name, info)
 }
 \arguments{
 \item{object}{Object of class "xgb.DMatrix"}
@@ -23,7 +22,7 @@ setinfo(object, ...)
 Set information of an xgb.DMatrix object
 }
 \details{
-It can be one of the following:
+The \code{name} field can be one of the following:
 
 \itemize{
     \item \code{label}: label Xgboost learn from ;
@@ -36,9 +35,10 @@ It can be one of the following:
 data(agaricus.train, package='xgboost')
 train <- agaricus.train
 dtrain <- xgb.DMatrix(train$data, label=train$label)
+
 labels <- getinfo(dtrain, 'label')
 setinfo(dtrain, 'label', 1-labels)
 labels2 <- getinfo(dtrain, 'label')
-stopifnot(all(labels2 == 1-labels))
+stopifnot(all.equal(labels2, 1-labels))
 }
 
diff --git a/R-package/man/slice.Rd b/R-package/man/slice.xgb.DMatrix.Rd
similarity index 52%
rename from R-package/man/slice.Rd
rename to R-package/man/slice.xgb.DMatrix.Rd
index b17722115..c352203fb 100644
--- a/R-package/man/slice.Rd
+++ b/R-package/man/slice.xgb.DMatrix.Rd
@@ -1,22 +1,26 @@
 % Generated by roxygen2: do not edit by hand
-% Please edit documentation in R/slice.xgb.DMatrix.R
-\docType{methods}
+% Please edit documentation in R/xgb.DMatrix.R
 \name{slice}
+\alias{[.xgb.DMatrix}
 \alias{slice}
-\alias{slice,xgb.DMatrix-method}
+\alias{slice.xgb.DMatrix}
 \title{Get a new DMatrix containing the specified rows of
 orginal xgb.DMatrix object}
 \usage{
 slice(object, ...)
 
-\S4method{slice}{xgb.DMatrix}(object, idxset, ...)
+\method{slice}{xgb.DMatrix}(object, idxset, ...)
+
+\method{[}{xgb.DMatrix}(object, idxset, colset = NULL)
 }
 \arguments{
 \item{object}{Object of class "xgb.DMatrix"}
 
-\item{...}{other parameters}
+\item{...}{other parameters (currently not used)}
 
 \item{idxset}{a integer vector of indices of rows needed}
+
+\item{colset}{currently not used (columns subsetting is not available)}
 }
 \description{
 Get a new DMatrix containing the specified rows of
@@ -26,6 +30,12 @@ orginal xgb.DMatrix object
 data(agaricus.train, package='xgboost')
 train <- agaricus.train
 dtrain <- xgb.DMatrix(train$data, label=train$label)
-dsub <- slice(dtrain, 1:3)
+
+dsub <- slice(dtrain, 1:42)
+labels1 <- getinfo(dsub, 'label')
+dsub <- dtrain[1:42, ]
+labels2 <- getinfo(dsub, 'label')
+all.equal(labels1, labels2)
+
 }
 
diff --git a/R-package/man/xgb.DMatrix.Rd b/R-package/man/xgb.DMatrix.Rd
index 2e892cc6d..cdb8fdf62 100644
--- a/R-package/man/xgb.DMatrix.Rd
+++ b/R-package/man/xgb.DMatrix.Rd
@@ -7,8 +7,7 @@
 xgb.DMatrix(data, info = list(), missing = NA, ...)
 }
 \arguments{
-\item{data}{a \code{matrix} object, a \code{dgCMatrix} object or a character 
-indicating the data file.}
+\item{data}{a \code{matrix} object, a \code{dgCMatrix} object or a character representing a filename}
 
 \item{info}{a list of information of the xgb.DMatrix object}
 
@@ -18,7 +17,8 @@ value that represents missing value. Sometime a data use 0 or other extreme valu
 \item{...}{other information to pass to \code{info}.}
 }
 \description{
-Contruct xgb.DMatrix object from dense matrix, sparse matrix or local file.
+Contruct xgb.DMatrix object from dense matrix, sparse matrix 
+or local file (that was created previously by saving an \code{xgb.DMatrix}).
 }
 \examples{
 data(agaricus.train, package='xgboost')
diff --git a/R-package/src/xgboost_R.cc b/R-package/src/xgboost_R.cc
index 665fb5faa..846ad9f47 100644
--- a/R-package/src/xgboost_R.cc
+++ b/R-package/src/xgboost_R.cc
@@ -195,6 +195,14 @@ SEXP XGDMatrixNumRow_R(SEXP handle) {
   return ScalarInteger(static_cast<int>(nrow));
 }
 
+SEXP XGDMatrixNumCol_R(SEXP handle) {
+  bst_ulong ncol;
+  R_API_BEGIN();
+  CHECK_CALL(XGDMatrixNumCol(R_ExternalPtrAddr(handle), &ncol));
+  R_API_END();
+  return ScalarInteger(static_cast<int>(ncol));
+}
+
 // functions related to booster
 void _BoosterFinalizer(SEXP ext) {
   if (R_ExternalPtrAddr(ext) == NULL) return;
diff --git a/R-package/src/xgboost_R.h b/R-package/src/xgboost_R.h
index 123ebe028..6e1739464 100644
--- a/R-package/src/xgboost_R.h
+++ b/R-package/src/xgboost_R.h
@@ -83,10 +83,16 @@ XGB_DLL SEXP XGDMatrixGetInfo_R(SEXP handle, SEXP field);
 
 /*!
  * \brief return number of rows
- * \param handle a instance of data matrix
+ * \param handle an instance of data matrix
  */
 XGB_DLL SEXP XGDMatrixNumRow_R(SEXP handle);
 
+/*!
+ * \brief return number of columns
+ * \param handle an instance of data matrix
+ */
+XGB_DLL SEXP XGDMatrixNumCol_R(SEXP handle);
+
 /*!
  * \brief create xgboost learner
  * \param dmats a list of dmatrix handles that will be cached
diff --git a/R-package/tests/testthat/test_dmatrix.R b/R-package/tests/testthat/test_dmatrix.R
new file mode 100644
index 000000000..baead5099
--- /dev/null
+++ b/R-package/tests/testthat/test_dmatrix.R
@@ -0,0 +1,67 @@
+require(xgboost)
+
+context("testing xgb.DMatrix functionality")
+
+data(agaricus.test, package='xgboost')
+test_data <- agaricus.test$data[1:100,]
+test_label <- agaricus.test$label[1:100]
+
+test_that("xgb.DMatrix: basic construction, saving, loading", {
+  # from sparse matrix
+  dtest1 <- xgb.DMatrix(test_data, label=test_label)
+  # from dense matrix 
+  dtest2 <- xgb.DMatrix(as.matrix(test_data), label=test_label)
+  expect_equal(getinfo(dtest1, 'label'), getinfo(dtest2, 'label'))
+  
+  # save to a local file
+  tmp_file <- tempfile('xgb.DMatrix_')
+  expect_true(xgb.DMatrix.save(dtest1, tmp_file))
+  # read from a local file
+  dtest3 <- xgb.DMatrix(tmp_file)
+  unlink(tmp_file)
+  expect_equal(getinfo(dtest1, 'label'), getinfo(dtest3, 'label'))
+})
+
+test_that("xgb.DMatrix: getinfo & setinfo", {
+  dtest <- xgb.DMatrix(test_data)
+  expect_true(setinfo(dtest, 'label', test_label))
+  labels <- getinfo(dtest, 'label')
+  expect_equal(test_label, getinfo(dtest, 'label'))
+  
+  expect_true(length(getinfo(dtest, 'weight')) == 0)
+  expect_true(length(getinfo(dtest, 'base_margin')) == 0)
+
+  expect_true(setinfo(dtest, 'weight', test_label))
+  expect_true(setinfo(dtest, 'base_margin', test_label))
+  expect_true(setinfo(dtest, 'group', c(50,50)))
+  expect_error(setinfo(dtest, 'group', test_label))
+  
+  # providing character values will give a warning
+  expect_warning( setinfo(dtest, 'weight', rep('a', nrow(test_data))) )
+  
+  # any other label should error
+  expect_error(setinfo(dtest, 'asdf', test_label))
+})
+
+test_that("xgb.DMatrix: slice, dim", {
+  dtest <- xgb.DMatrix(test_data, label=test_label)
+  expect_equal(dim(dtest), dim(test_data))
+  dsub1 <- slice(dtest, 1:42)
+  expect_equal(nrow(dsub1), 42)
+  expect_equal(ncol(dsub1), ncol(test_data))
+  
+  dsub2 <- dtest[1:42,]
+  expect_equal(dim(dtest), dim(test_data))
+  expect_equal(getinfo(dsub1, 'label'), getinfo(dsub2, 'label'))
+})
+
+test_that("xgb.DMatrix: colnames", {
+  dtest <- xgb.DMatrix(test_data, label=test_label)
+  expect_equal(colnames(dtest), colnames(test_data))
+  expect_error( colnames(dtest) <- 'asdf')
+  new_names <- make.names(1:ncol(test_data))
+  expect_silent( colnames(dtest) <- new_names)
+  expect_equal(colnames(dtest), new_names)
+  expect_silent(colnames(dtest) <- NULL)
+  expect_null(colnames(dtest))
+})