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# program spuRs/resources/scripts/hit_miss.r
hit_miss <- function(ftn, a, b, f.min, f.max, n) {
# Monte-Carlo integration using the hit and miss method
# ftn is a function of one variable
# [a, b] is the range of integration
# f.min and f.max are bounds on ftn over the range [a, b]
# that is f.min <= ftn(x) <= f.max for all x in [a, b]
# n is the number of samples used in the estimation
# that is the number of calls made to the function ftn
Z.sum <- 0
for (i in 1:n) {
X <- runif(1, a, b)
Y <- runif(1, f.min, f.max)
Z <- (ftn(X) >= Y)
Z.sum <- Z.sum + Z
}
I <- (b - a)*f.min + (Z.sum/n)*(b - a)*(f.max - f.min)
return(I)
}
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