twocor: Compute a .95 confidence interval for the difference between...
In WRS: A package of R.R. Wilcox' robust statistics functions

The function corfun is any function that returns a correlation coefficient in corfun$cor. The functions pbcor and wincor follow this convention.

For Pearson's correlation, use the function twopcor instead.

The default number of bootstrap samples is nboot=599

1	twocor(x1, y1, x2, y2, corfun = pbcor, nboot = 599, alpha = 0.05, ...)

`x1`
`y1`
`x2`
`y2`
`corfun`
`nboot`
`alpha`
`...`

##---- Should be DIRECTLY executable !! ----
##-- ==>  Define data, use random,
##--	or do  help(data=index)  for the standard data sets.

## The function is currently defined as
function (x1, y1, x2, y2, corfun = pbcor, nboot = 599, alpha = 0.05, 
    SEED = T, ...) 
{
    if (SEED) 
        set.seed(2)
    print("Taking bootstrap samples. Please wait.")
    data1 <- matrix(sample(length(y1), size = length(y1) * nboot, 
        replace = T), nrow = nboot)
    bvec1 <- apply(data1, 1, corbsub, x1, y1, corfun, ...)
    data2 <- matrix(sample(length(y2), size = length(y2) * nboot, 
        replace = T), nrow = nboot)
    bvec2 <- apply(data2, 1, corbsub, x2, y2, corfun, ...)
    bvec <- bvec1 - bvec2
    bsort <- sort(bvec)
    term <- alpha/2
    ihi <- floor((1 - term) * nboot + 0.5)
    ilow <- floor(term * nboot + 0.5)
    corci <- 1
    corci[1] <- bsort[ilow]
    corci[2] <- bsort[ihi]
    r1 <- corfun(x1, y1)$cor
    r2 <- corfun(x2, y2)$cor
    reject <- "NO"
    if (corci[1] > 0 || corci[2] < 0) 
        reject = "YES"
    list(r1 = r1, r2 = r2, ci.dif = corci, reject = reject)
  }