my specific question is:
I am attempting to create a bootstrap procedure for a finite sample using the
theory of Rao and Wu, JASA (1988) that replicates within each strata (h) n_h - 1
times. I am able to sample n_h times using an innitial call to the resample
function I suspect that it has to do with providing extra info to the FUN
function but this seems to only allow one value i.e tapply(test, class, mean,
trim = 0.1)
i want to be able to have a different value of n for each
sampler <- function(x)
{ sample(x, replace = T)
}
raoboot <- function (datavar, statavar, weight, nboot)
{
i <- 1
sdatavar <- sort(datavar)
sstratavar <- sort(statavar)
sweight <- sort(weight)
sdatavarwght <- sdatavar*sweight
stramn <- tapply(sdatavar, sstratavar, mean)
meanvect <- rep(0, times = nboot)
while (i < nboot)
{ #vector of resampled observations
vectobsrestemp <- tapply(sdatavarwght, sstratavar, resampler)
vectobsres <- unlist(vectobsrestemp)
meanvect[i] <- mean(vectobsres)
i <- i + 1
}
repvectboot <- rep(mean(meanvect), times = i)
vb <- sum((repvectboot - meanvect)^2)/(i -1)
}