improve doc for se prediction

R/predict.R

@@ -30,7 +30,7 @@
 ##' Prediction with new data and a saved forest from Ranger.
 ##' 
 ##' For \code{type = 'response'} (the default), the predicted classes (classification), predicted numeric values (regression), predicted probabilities (probability estimation) or survival probabilities (survival) are returned. 
-##' For \code{type = 'se'}, the standard error of the predictions are returned (regression only).
+##' For \code{type = 'se'}, the standard error of the predictions are returned (regression only). The jackknife-after-bootstrap is used to estimate the standard errors based on out-of-bag predictions. See Wager et al. (2014) for details.
 ##' For \code{type = 'terminalNodes'}, the IDs of the terminal node in each tree for each observation in the given dataset are returned.
 ##' 
 ##' For classification and \code{predict.all = TRUE}, a factor levels are returned as numerics.
@@ -58,6 +58,11 @@
 ##'       \code{treetype}    \tab Type of forest/tree. Classification, regression or survival. \cr
 ##'       \code{num.samples}     \tab Number of samples.
 ##'   }
+##' @references
+##' \itemize{
+##'   \item Wright, M. N. & Ziegler, A. (2017). ranger: A Fast Implementation of Random Forests for High Dimensional Data in C++ and R. J Stat Softw 77:1-17. \url{http://dx.doi.org/10.18637/jss.v077.i01}.
+##'   \item Wager, S., Hastie T., & Efron, B. (2014). Confidence Intervals for Random Forests: The Jackknife and the Infinitesimal Jackknife. J Mach Learn Res 15:1625-1651. \url{http://jmlr.org/papers/v15/wager14a.html}.
+##'   }
 ##' @seealso \code{\link{ranger}}
 ##' @author Marvin N. Wright
 ##' @export
@@ -371,7 +376,7 @@ predict.ranger.forest <- function(object, data, predict.all = FALSE,
 ##' Prediction with new data and a saved forest from Ranger.
 ##' 
 ##' For \code{type = 'response'} (the default), the predicted classes (classification), predicted numeric values (regression), predicted probabilities (probability estimation) or survival probabilities (survival) are returned. 
-##' For \code{type = 'se'}, the standard error of the predictions are returned (regression only).
+##' For \code{type = 'se'}, the standard error of the predictions are returned (regression only). The jackknife-after-bootstrap is used to estimate the standard errors based on out-of-bag predictions. See Wager et al. (2014) for details.
 ##' For \code{type = 'terminalNodes'}, the IDs of the terminal node in each tree for each observation in the given dataset are returned.
 ##' 
 ##' For classification and \code{predict.all = TRUE}, a factor levels are returned as numerics.
@@ -398,6 +403,11 @@ predict.ranger.forest <- function(object, data, predict.all = FALSE,
 ##'       \code{treetype}    \tab Type of forest/tree. Classification, regression or survival. \cr
 ##'       \code{num.samples}     \tab Number of samples.
 ##'   }
+##' @references
+##' \itemize{
+##'   \item Wright, M. N. & Ziegler, A. (2017). ranger: A Fast Implementation of Random Forests for High Dimensional Data in C++ and R. J Stat Softw 77:1-17. \url{http://dx.doi.org/10.18637/jss.v077.i01}.
+##'   \item Wager, S., Hastie T., & Efron, B. (2014). Confidence Intervals for Random Forests: The Jackknife and the Infinitesimal Jackknife. J Mach Learn Res 15:1625-1651. \url{http://jmlr.org/papers/v15/wager14a.html}.
+##'   }
 ##' @seealso \code{\link{ranger}}
 ##' @author Marvin N. Wright
 ##' @export