R: Plot likelihood ratio test statistics from supervised...

superpc.plotred.lrtest {superpc} | R Documentation

## Plot likelihood ratio test statistics from supervised principal components predictor

### Description

Plot likelihood ratio test statistics from supervised principal components predictor

### Usage

    superpc.plotred.lrtest(object.lrtestred, call.win.metafile=FALSE)

### Arguments

`object.lrtestred` | Output from either superpc.predict.red or superpc.predict.redcv
`call.win.metafile` | Used only by PAM Excel interface call to function

### Author(s)

Eric Bair and Robert Tibshirani

### References

~put references to the literature/web site here ~

### Examples

    set.seed(332)
    #generate some data

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

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

    fit<- superpc.predict(a, data, data.test, threshold=1.0, n.components=1, prediction.type="continuous")

    fit.red<- superpc.predict.red(a, data, data.test, .6)

    fit.redcv<- superpc.predict.red.cv(fit.red, aa,  data,  .6)

    superpc.plotred.lrtest(fit.redcv)

[Package superpc version 1.09 Index]