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## BART: Bayesian Additive Regression Trees
## Copyright (C) 2017 Robert McCulloch and Rodney Sparapani
## This program is free software; you can redistribute it and/or modify
## it under the terms of the GNU General Public License as published by
## the Free Software Foundation; either version 2 of the License, or
## (at your option) any later version.
## This program is distributed in the hope that it will be useful,
## but WITHOUT ANY WARRANTY; without even the implied warranty of
## MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
## GNU General Public License for more details.
## You should have received a copy of the GNU General Public License
## along with this program; if not, a copy is available at
## https://www.R-project.org/Licenses/GPL-2
predict.recurbart <- function(object, newdata, mc.cores=1, openmp=(mc.cores.openmp()>0), ...) {
##if(class(newdata) != "matrix") stop("newdata must be a matrix")
p <- length(object$treedraws$cutpoints)
if(p!=ncol(newdata))
stop(paste0('The number of columns in newdata must be equal to ', p))
if(.Platform$OS.type == "unix") mc.cores.detected <- detectCores()
else mc.cores.detected <- NA
if(!is.na(mc.cores.detected) && mc.cores>mc.cores.detected) mc.cores <- mc.cores.detected
if(.Platform$OS.type != "unix" || openmp || mc.cores==1) call <- recur.pwbart
else call <- mc.recur.pwbart
if(length(object$binaryOffset)==0) object$binaryOffset=object$offset
return(call(newdata, object$treedraws, mc.cores=mc.cores,
binaryOffset=object$binaryOffset,
type=object$type, ...))
}
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