Plot likelihood ratio test statistics from supervised principal components predictor

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Description

Plot likelihood ratio test statistics from supervised principal components predictor

Usage

1
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

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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)