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# This function uses a resampling approach for computing
# the probability that at least two people will have
# the same birthday in a group of "n" people.
pbday <- function(n) {
ntests <- 1000
pop <- 1:365
anydup <- function(i) any(duplicated(sample(pop, n, replace=TRUE)))
sum(sapply(seq(ntests), anydup)) / ntests
}
# Execute the pbday function for group sizes 1 to 100
x <- 1:100
# Sequential version
if (FALSE) {
prob <- sapply(x, pbday)
}
# Parallel version
if (TRUE) {
library(nws)
s <- sleigh()
prob <- unlist(eachElem(s, pbday, x))
}
# Display a plot of the probability vs. group size
plot(x, prob, main='Birthday Paradox', xlab='Group Size', ylab='Probability')
# Compare with the analytical results, using the
# standard R "pbirthday" function.
# The results are only expected to be close.
print(all.equal(prob, sapply(x, pbirthday)))
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