roc.plot <- 
function(x,y, plot.it = T, log = "xy", version=0, ...) {
# x and y are two vectors of test results
# x are results under null hypothesis
# y are results under alternative hypothesis
# want to plot p(x > z) vs p(y < z) for all
# possibilities z
# choose z as values of x or y, whichever is shorter
# this version doesn't worry about ties
# graphical parameters may be passed in via ...
# version=0 False alarms/ missing alarms 
# version=1 Sensitivity/ specificity
nx <- length(x)
ny <- length(y)
n <- nx + ny
if(nx < ny) {
    z <- sort(x)
    Z <- y
    nz <- nx
    nZ <- ny
  }
  else {
    z <- sort(y)
    Z <- x
    nz <- ny
    nZ <- nx
  }
zrank <- (1:n)[c(rep(T, nz), rep(F, nZ))[order(c(z, Z))]]
pz <- (1:nz - .5) / nz
pZ <- (zrank - 1:nz)/nZ
keep <- (pZ > 0) & (pZ < 1)
pz <- pz[keep]
pZ <- pZ[keep]
if(nx < ny) {
    px <- 1 - pz
    py <- pZ
  }
  else {
    px <- 1 - pZ
    py <- pz
  }

if (version==1) {
   py<- 1-py
   px<- 1-px
}

if(plot.it) {
  if (version==0) 
    plot(px, py, log=log, 
         xlab = "False Positive", ylab = "False Negative", 
         xlim=c(.005,1),ylim=c(.001,1),...)
  else 
    plot(px, py, log=log, 
         xlab = "Specificity", ylab = "Sensitivity", 
         xlim=c(.005,1),ylim=c(.001,1),...)
}

# note: if plot.it is false, you can add a curve to another plot
# with the command "lines(roc.plot(x, y, F))"
invisible(list(x = px, y = py))
}