Plot.peperr.curves {c060} | R Documentation |
Plot method for prediction error curves of a peperr object
Description
Plots individual and aggregated prediction error estimates based on bootstrap samples.
Usage
Plot.peperr.curves(x, at.risk=TRUE, allErrors=FALSE,
bootRuns=FALSE, bootQuants=TRUE, bootQuants.level=0.95, leg.cex=0.7,...)
Arguments
x |
|
at.risk |
number at risk to be display. default is TRUE. |
allErrors |
Display .632, no information and average out-of-bag error in addition. default is FALSE. |
bootRuns |
Display individual out-of-bag bootstrap samples. default is FALSE. |
bootQuants |
Display pointwise out-of-bag bootstrap quantiles as shaded area. default is TRUE. |
bootQuants.level |
Quantile probabilities for pointwise out-of-bag bootstrap quantiles. default is 0.95, i.e. 2.5% and 97.5% quantiles. |
leg.cex |
size of legend text |
... |
additional arguments, not used. |
Details
This function is literally taken from plot.peperr
in the peperr
package.
The display of prediction error curves is adapted to allow for numbers at risk and pointwise bootstrap quantiles.
Author(s)
Thomas Hielscher t.hielscher@dkfz.de
References
Sill M., Hielscher T., Becker N. and Zucknick M. (2014), c060: Extended Inference with Lasso and Elastic-Net Regularized Cox and Generalized Linear Models, Journal of Statistical Software, Volume 62(5), pages 1–22. doi:10.18637/jss.v062.i05
See Also
Examples
## Not run:
# example from glmnet package
set.seed(10101)
library(glmnet)
library(survival)
library(peperr)
N=1000;p=30
nzc=p/3
x=matrix(rnorm(N*p),N,p)
beta=rnorm(nzc)
fx=x[,seq(nzc)]
hx=exp(fx)
ty=rexp(N,hx)
tcens=rbinom(n=N,prob=.3,size=1)# censoring indicator
y=Surv(ty,1-tcens)
peperr.object <- peperr(response=y, x=x,
fit.fun=fit.glmnet, args.fit=list(family="cox"),
complexity=complexity.glmnet,
args.complexity=list(family="cox",nfolds=10),
indices=resample.indices(n=N, method="sub632", sample.n=10))
# pointwise bootstrap quantiles and all error types
Plot.peperr.curves(peperr.object, allErrors=TRUE)
# individual bootstrap runs and selected error types
Plot.peperr.curves(peperr.object, allErrors=FALSE, bootRuns=TRUE)
## End(Not run)