--- a
+++ b/partyMod/man/ctree_memory.Rd
@@ -0,0 +1,47 @@
+\name{Memory Allocation}
+\alias{ctree_memory}
+\title{ Memory Allocation }
+\description{
+
+    This function sets up the memory needed for tree growing. It might be 
+    convenient to allocate memory only once but build multiple trees.
+}
+\usage{
+ctree_memory(object, MPinv = FALSE)
+}
+\arguments{
+  \item{object}{an object of class \code{LearningSample}.}
+  \item{MPinv}{a logical indicating whether memory for the Moore-Penrose
+               inverse of covariance matrices should be allocated. }
+}
+\details{
+
+  This function is normally not to be called by users. However, for
+  performance reasons it might be nice to allocate memory and re-fit trees
+  using the same memory for the computations. Below is an example.
+
+}
+\value{
+  An object of class \code{TreeFitMemory}.
+}
+\examples{
+
+    set.seed(290875)
+
+    ### setup learning sample
+    airq <- subset(airquality, !is.na(Ozone))
+    ls <- dpp(conditionalTree, Ozone ~ ., data = airq)
+
+    ### setup memory and controls 
+    mem <- ctree_memory(ls)
+    ct <- ctree_control(teststat = "max")
+
+    ### fit 50 trees on bootstrap samples
+    bs <- rmultinom(50, nrow(airq), rep(1, nrow(airq))/nrow(airq))
+    storage.mode(bs) <- "double"
+    cfit <- conditionalTree@fit
+    ens <- apply(bs, 2, function(w) cfit(ls, ct, weights = w, 
+                                         fitmem = mem))
+
+}
+\keyword{misc}