R/roc.R

In gbonte/gbcode: Code from the handbook "Statistical foundations of machine learning"

ROC<-function(){
  mu.p<-2
  sd.p<-1

  mu.n<--1
  sd.n<-1


  TT<-seq(-10,10,by=.05)
  FPR<-numeric(length(TT))
  SE<-numeric(length(TT))
  R<-100000
  for (tt in 1:length(TT)){
    thr<-TT[tt]
    DNp<-rnorm(R,mu.p,sd.p)
    DNn<-rnorm(R,mu.n,sd.n)
    FN<-length(which(DNp<thr))
    FP<-length(which(DNn>thr))
    TN<-length(which(DNn<thr))
    TP<-length(which(DNp>thr))
    FPR[tt]<-FP/(FP+TN)
    SE[tt]<-TP/(TP+FN)
  }


  plot(FPR,SE)
}