Hi,
I'm trying to write a code (see below) to randomly resample measurements of
one variable (say here the variable "counts" in the data frame
"dat") with
different resampled subsample sizes.
The code works fine for a single resampled subsample size (in the code below
= 10).
I then tried to generalize this by writing a function with a loop, where in
each loop the function should do the calculations with increasing subsample
size (say for j in 1:100).
Problem is, I can't tell R to write the results of each of these loops. As a
result, the function always keeps the results of the last loop (with j=100).
Many thanks in advance for any suggestion.
# Creating data frame with "counts" and "depths"
test <- matrix(rep(1, 1000))
depths <- matrix(1:1000)
dat <- cbind(test, depths)
rm(depths, test)
colnames(dat) <- c("counts", "depths")
dat <- as.data.frame(dat)
### Easy code to resample 999 times 10 "counts" from dat
require(MASS)
# Makes sums and var based on 999 resampled counts and stores results in a
matrix
# with sums and vars in 999 rows and 2 columns - THIS WORKS
resamples10 <- lapply(1:999, function(i) sample(dat$counts, 10, replace=T))
r10.stat <- cbind(sapply(resamples10, sum), sapply(resamples10, var),
sapply(resamples10, mean))
colnames(r10.stat) <- c("r10.sum", "r10.var",
"r10.mean")
### NEED to generalize this for different sample sizes
# Creates the resample function with arguments "data", stat.
# by default, num = size of resampled subsample varies for j in 1:100
# CAN'T tell him to store all sums of different sample sizes in one
data.frame
require(MASS)
b.stat <- function(data, stat) {
for (j in 1:100){
rj.repl <- lapply(1:999, function(i) sample(data, j, replace=T))
rj.stat <- sapply(rj.repl, stat)
rj.stderr <- sqrt(var(rj.stat))
list(std.err=rj.stderr, resamples=rj.repl, stats=rj.stat)
}
b.sum <- cbind([, rj.stat])
}
b.sum <- b.stat(dat$counts, sum)
--
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