58 lines
2.0 KiB
Plaintext
58 lines
2.0 KiB
Plaintext
|
|
||
|
|
R Under development (unstable) (2019-04-05 r76323) -- "Unsuffered Consequences"
|
||
|
|
Copyright (C) 2019 The R Foundation for Statistical Computing
|
||
|
|
Platform: x86_64-pc-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 "return.all" argument of xpred
|
||
|
|
> # The data set has the virtue of continuous, categorical, and missings
|
||
|
|
> #
|
||
|
|
> library(rpart)
|
||
|
|
> require(survival)
|
||
|
|
Loading required package: survival
|
||
|
|
> set.seed(10)
|
||
|
|
>
|
||
|
|
> fit1 <- rpart(Surv(pgtime, pgstat) ~ age + eet + g2+grade+gleason +ploidy,
|
||
|
|
+ stagec, method='poisson')
|
||
|
|
>
|
||
|
|
> xgrp <- rep(1:3, length=nrow(stagec)) # explicitly set the xval groups
|
||
|
|
>
|
||
|
|
> xfit1 <- xpred.rpart(fit1, xval=xgrp, return.all=T)
|
||
|
|
> xfit2 <- array(0, dim=dim(xfit1))
|
||
|
|
> cplist <- as.numeric(dimnames(xfit1)[[2]])
|
||
|
|
>
|
||
|
|
> for (i in 1:3) {
|
||
|
|
+ tfit <- rpart(Surv(pgtime, pgstat) ~ age + eet + g2+grade+gleason +ploidy,
|
||
|
|
+ stagec, method='poisson', subset=(xgrp !=i))
|
||
|
|
+ # xvals are actually done on the absolute risk (node's risk /n), not on
|
||
|
|
+ # the rescaled risk ((node risk)/ (top node risk)) which is the basis
|
||
|
|
+ # for the printed CP. To get the right answer we need to rescale.
|
||
|
|
+ cp2 <- cplist * (fit1$frame$dev[1] / fit1$frame$n[1]) /
|
||
|
|
+ (tfit$frame$dev[1] / tfit$frame$n[1])
|
||
|
|
+
|
||
|
|
+ for (j in 1:length(cp2)) {
|
||
|
|
+ tfit2 <- prune(tfit, cp=cp2[j])
|
||
|
|
+ temp <- predict(tfit2, newdata=stagec[xgrp==i,], type='matrix')
|
||
|
|
+ xfit2[xgrp==i, j,] <- temp
|
||
|
|
+ }
|
||
|
|
+ }
|
||
|
|
>
|
||
|
|
> all.equal(xfit1, xfit2, check.attributes=FALSE)
|
||
|
|
[1] TRUE
|
||
|
|
>
|
||
|
|
> proc.time()
|
||
|
|
user system elapsed
|
||
|
|
0.752 0.035 0.782
|