superpc.plotred.lrtest {superpc} | R Documentation |
Plot likelihood ratio test statistics from supervised principal components predictor
superpc.plotred.lrtest(object.lrtestred, call.win.metafile=FALSE)
object.lrtestred |
Output from either superpc.predict.red or superpc.predict.redcv |
call.win.metafile |
Used only by PAM Excel interface call to function |
~~further notes~~
Eric Bair and Robert Tibshirani
~put references to the literature/web site here ~
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)