Calls with DUP:
   .C("classRF", x = x, xdim = as.integer(c(p, n)), y = as.integer(y), 
       nclass = as.integer(nclass), ncat = as.integer(ncat), maxcat = as.integer(maxcat), 
       sampsize = as.integer(sampsize), strata = if (Stratify) as.integer(strata) else integer(1), 
       Options = as.integer(c(addclass, importance, localImp, proximity, 
           oob.prox, do.trace, keep.forest, replace, Stratify, keep.inbag)), 
       ntree = as.integer(ntree), mtry = as.integer(mtry), ipi = as.integer(ipi), 
       classwt = as.double(cwt), cutoff = as.double(threshold), 
       nodesize = as.integer(nodesize), outcl = integer(nsample), 
       counttr = integer(nclass * nsample), prox = prox, impout = impout, 
       impSD = impSD, impmat = impmat, nrnodes = as.integer(nrnodes), 
       ndbigtree = integer(ntree), nodestatus = integer(nt * nrnodes), 
       bestvar = integer(nt * nrnodes), treemap = integer(nt * 2 * 
           nrnodes), nodepred = integer(nt * nrnodes), xbestsplit = double(nt * 
           nrnodes), errtr = double((nclass + 1) * ntree), testdat = as.integer(testdat), 
       xts = as.double(xtest), clts = as.integer(ytest), nts = as.integer(ntest), 
       countts = double(nclass * ntest), outclts = as.integer(numeric(ntest)), 
       labelts = as.integer(labelts), proxts = proxts, errts = error.test, 
       inbag = if (keep.inbag) matrix(integer(n * ntree), n) else integer(n), 
       coefReg = as.double(coefReg), flagReg = as.integer(flagReg), 
       varUsedAll = as.integer(varUsedAll), DUP = FALSE, PACKAGE = "RRF")
   .C("regRF", x, as.double(y), as.integer(c(n, p)), as.integer(sampsize), 
       as.integer(nodesize), as.integer(nrnodes), as.integer(ntree), 
       as.integer(mtry), as.integer(c(importance, localImp, nPerm)), 
       as.integer(ncat), as.integer(maxcat), as.integer(do.trace), 
       as.integer(proximity), as.integer(oob.prox), as.integer(corr.bias), 
       ypred = double(n), impout = impout, impmat = impmat, impSD = impSD, 
       prox = prox, ndbigtree = integer(ntree), nodestatus = matrix(integer(nrnodes * 
           nt), ncol = nt), leftDaughter = matrix(integer(nrnodes * 
           nt), ncol = nt), rightDaughter = matrix(integer(nrnodes * 
           nt), ncol = nt), nodepred = matrix(double(nrnodes * nt), 
           ncol = nt), bestvar = matrix(integer(nrnodes * nt), ncol = nt), 
       xbestsplit = matrix(double(nrnodes * nt), ncol = nt), mse = double(ntree), 
       keep = as.integer(c(keep.forest, keep.inbag)), replace = as.integer(replace), 
       testdat = as.integer(testdat), xts = xtest, ntest = as.integer(ntest), 
       yts = as.double(ytest), labelts = as.integer(labelts), ytestpred = double(ntest), 
       proxts = proxts, msets = double(if (labelts) ntree else 1), 
       coef = double(2), oob.times = integer(n), inbag = if (keep.inbag) matrix(integer(n * 
           ntree), n) else integer(1), DUP = FALSE, PACKAGE = "RRF")
   .C("regForest", as.double(x), ypred = double(ntest), as.integer(mdim), 
       as.integer(ntest), as.integer(ntree), object$forest$leftDaughter, 
       object$forest$rightDaughter, object$forest$nodestatus, nrnodes, 
       object$forest$xbestsplit, object$forest$nodepred, object$forest$bestvar, 
       object$forest$ndbigtree, object$forest$ncat, as.integer(maxcat), 
       as.integer(predict.all), treepred = as.double(treepred), 
       as.integer(proximity), proximity = as.double(proxmatrix), 
       nodes = as.integer(nodes), nodexts = as.integer(nodexts), 
       DUP = FALSE, PACKAGE = "RRF")
   .C("classForest", mdim = as.integer(mdim), ntest = as.integer(ntest), 
       nclass = as.integer(object$forest$nclass), maxcat = as.integer(maxcat), 
       nrnodes = as.integer(nrnodes), jbt = as.integer(ntree), xts = as.double(x), 
       xbestsplit = as.double(object$forest$xbestsplit), pid = object$forest$pid, 
       cutoff = as.double(cutoff), countts = as.double(countts), 
       treemap = as.integer(aperm(object$forest$treemap, c(2, 1, 
           3))), nodestatus = as.integer(object$forest$nodestatus), 
       cat = as.integer(object$forest$ncat), nodepred = as.integer(object$forest$nodepred), 
       treepred = as.integer(treepred), jet = as.integer(numeric(ntest)), 
       bestvar = as.integer(object$forest$bestvar), nodexts = as.integer(nodexts), 
       ndbigtree = as.integer(object$forest$ndbigtree), predict.all = as.integer(predict.all), 
       prox = as.integer(proximity), proxmatrix = as.double(proxmatrix), 
       nodes = as.integer(nodes), DUP = FALSE, PACKAGE = "RRF")
DUP is no longer supported and will be ignored.