This function sets up the memory needed for tree growing. It might be convenient to allocate memory only once but build multiple trees.
an object of class
a logical indicating whether memory for the Moore-Penrose inverse of covariance matrices should be allocated.
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.
An object of class
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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))