R: Plot output from superpc.cv

superpc.plotcv {superpc} | R Documentation

## Plot output from superpc.cv

### Description

Plots pre-validation results from plotcv, to aid in choosing best threshold

### Usage

    superpc.plotcv(object, cv.type=c("full","preval"),smooth = TRUE, smooth.df = 10, call.win.metafile=FALSE, ...)

### Arguments

`object` | Object returned by superpc.cv
`cv.type` | Type of cross-validation used- "full" (Default; this is "standard" cross-validation; recommended) and "preval"- pre-validation
`smooth` | Should plot be smoothed? Only relevant to "preval". Default FALSE.
`smooth.df` | Degrees of freedom for smooth.spline, default 10. If NULL, then degrees of freedom is estimated by cross-validation.
`call.win.metafile` | Ignore: for use by PAM Excel program
`...` | Additional plotting args to be passed to matplot

### Author(s)

Eric Bair and Robert Tibshirani

### Examples

    set.seed(332)
    x<-matrix(rnorm(1000*40),ncol=40)
    y<-10+svd(x[1:60,])$v[,1]+ .1*rnorm(40)
    censoring.status<- sample(c(rep(1,30),rep(0,10)))

    featurenames <- paste("feature",as.character(1:1000),sep="")
    data<-list(x=x,y=y, censoring.status=censoring.status, featurenames=featurenames)

    a<- superpc.train(data, type="survival")
    aa<-superpc.cv(a,data)

    superpc.plotcv(aa)

[Package superpc version 1.09 Index]