Trying around with the boot package in R and it does not accomplish what I want, it just returns the same value. I have read the documentation and checked the first example which seems to be the same, but I don't get any bootstrapped results, just the original value is returned. My example:
dat <- data.frame(A = rnorm(100), B = runif(100))
booty <- function(x, ind) sum(x$A)/sum(x$B)
boot_out <- boot(dat, booty, R = 50, stype = "w")
Like I've said in the comment, you must use the index, in this case ind, to subset the dataset passed to the bootstrap statistic function, sum(x$A[ind])/sum(x$B[ind]).
The full function would then become
booty <- function(x, ind) sum(x$A[ind])/sum(x$B[ind])
Two notes.
One, the stype = "i" argument states that the second argument to booty is a vector of indices, which, I believe, is what you want, not a vector of weights, stype = "w".
Also, in order to have reproducible results, the RNG seed should be set before calling boot or RNG functions. Something like the following.
set.seed(4237)
dat <- data.frame(A = rnorm(100), B = runif(100))
boot_out <- boot(dat, booty, R = 50, stype = "i")