party (version 1.0-25)

Memory Allocation: 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

object

an object of class LearningSample.

MPinv

a logical indicating whether memory for the Moore-Penrose inverse of covariance matrices should be allocated.

Value

An object of class TreeFitMemory.

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.

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))