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R version 2.15.0 (2012-03-30)Copyright (C) 2012 The R Foundation for Statistical ComputingISBN 3-900051-07-0Platform: x86_64-unknown-linux-gnu (64-bit)R is free software and comes with ABSOLUTELY NO WARRANTY.You are welcome to redistribute it under certain conditions.Type 'license()' or 'licence()' for distribution details.R is a collaborative project with many contributors.Type 'contributors()' for more information and'citation()' on how to cite R or R packages in publications.Type 'demo()' for some demos, 'help()' for on-line help, or'help.start()' for an HTML browser interface to help.Type 'q()' to quit R.> #> # Test out the rescaling done for Surv objects> #> library(rpart)> require(survival)Loading required package: survivalLoading required package: splines>> aeq <- function(x,y, ...) all.equal(as.vector(x), as.vector(y), ...)> tdata <- data.frame(time=c(1,4,3,2,5,7,8,9,4), status=c(0,1,1,0,0,1,1,0,1),+ x=1:9)> fit2 <- rpart.exp(Surv(tdata$time, tdata$status), NULL, wt=rep(1,9))>> #> # Here is what it should be, in order> # for the intervals (0,3], (3,4], (4,7], (7,9]> deaths <- c( 1, 2, 1, 1)> pyears <- c(24, 6, 10, 3)> rate <- deaths/pyears> cumhaz <- cumsum(c(0, rate*c(3,1,3,2)))>> aeq(fit2$y[,2], tdata$status)[1] TRUE> aeq(fit2$y[,1], approx(c(0,3,4,7,9), cumhaz, tdata$time)$y)[1] TRUE>>>>>>> proc.time()user system elapsed0.260 0.063 0.387